Relevant bibliographies by topics / Ordinary least square

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Ordinary least square'

Author: Grafiati
Published: 4 June 2021
Last updated: 3 February 2022

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Journal articles on the topic "Ordinary least square"

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Park, Min Jung, and Soon Man Kwon. "Socioeconomic Determinants of Korean Medicine Ambulatory Services: Comparing Panel Fixed Effect Model with Pooled Ordinary Least Square." Health Policy and Management 24, no. 1 (March 31, 2014): 47–55. http://dx.doi.org/10.4332/kjhpa.2014.24.1.47.

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Benouaz, T., and O. Arino. "Least square approximation of a nonlinear ordinary differential equation." Computers & Mathematics with Applications 31, no. 8 (April 1996): 69–84. http://dx.doi.org/10.1016/0898-1221(96)00032-6.

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Rashid, Intan Maizura Abd. "Determinants of FDI Inflows in Agriculture Sector Using Pooled Ordinary Least Square (OLS), Pooled Generalized Least Square (GLS), Augmented Dickey-Fuller (ADF) and Philips-perron Unit Root Test." International Journal of Psychosocial Rehabilitation 24, no. 5 (April 20, 2020): 2560–67. http://dx.doi.org/10.37200/ijpr/v24i5/pr201955.

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Tabass, Manije Sanei, and G. R. Mohtashami Borzadaran. "A comparison of generalised maximum entropy and ordinary least square." International Journal of Information and Decision Sciences 10, no. 4 (2018): 297. http://dx.doi.org/10.1504/ijids.2018.095495.

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Tabass, Manije Sanei, and G. R. Mohtashami Borzadaran. "A comparison of generalised maximum entropy and ordinary least square." International Journal of Information and Decision Sciences 10, no. 4 (2018): 297. http://dx.doi.org/10.1504/ijids.2018.10016400.

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Tong, Hongzhi, Di-Rong Chen, and Fenghong Yang. "Least Square Regression with lp-Coefficient Regularization." Neural Computation 22, no. 12 (December 2010): 3221–35. http://dx.doi.org/10.1162/neco_a_00044.

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The selection of the penalty functional is critical for the performance of a regularized learning algorithm, and thus it deserves special attention. In this article, we present a least square regression algorithm based on lp-coefficient regularization. Comparing with the classical regularized least square regression, the new algorithm is different in the regularization term. Our primary focus is on the error analysis of the algorithm. An explicit learning rate is derived under some ordinary assumptions.
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Sadoghi Yazdi, Hadi, Morteza Pakdaman, and Hamed Modaghegh. "Unsupervised kernel least mean square algorithm for solving ordinary differential equations." Neurocomputing 74, no. 12-13 (June 2011): 2062–71. http://dx.doi.org/10.1016/j.neucom.2010.12.026.

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Abramov, A. A., and L. F. Yukhno. "The Least Square Method for Systems of Linear Ordinary Differential Equations." Computational Mathematics and Mathematical Physics 59, no. 6 (June 2019): 915–25. http://dx.doi.org/10.1134/s0965542519060022.

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Enjarwati, Tria. "IMPACT OF GOVERNMENT FISCAL SPACE AND MANPOWER TO THE GROSS DOMESTIC PRODUCTS OF INDONESIA PERIOD 1990-2015." Journal of Developing Economies 3, no. 1 (July 31, 2018): 20. http://dx.doi.org/10.20473/jde.v3i1.8562.

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To purpose of this study was to examine and analyze the effect of fiscal space and labour absorption to Indonesia Gross Domestic Product (GDP) within period 1990-2015. This study uses the least squares method or Ordinary Least Square (OLS) with time series data. Variables used in this study is the Gross Domestic Product (GDP) as the dependent variable, whereas for independent variables using the fiscal space and labour absorption. The results of regression calculations using the least squares method or Ordinary Least Square (OLS) in this study indicate that the fiscal space variable has a positive significant effect, and labour absorption variable has a positive significant effect to indonesia Gross Domestic Product (GDP).
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Yeniay, Özgür, Öznur İşçi, Atilla Göktaş, and M. Niyazi Çankaya. "Time Scale in Least Square Method." Abstract and Applied Analysis 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/354237.

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Study of dynamic equations in time scale is a new area in mathematics. Time scale tries to build a bridge between real numbers and integers. Two derivatives in time scale have been introduced and called as delta and nabla derivative. Delta derivative concept is defined as forward direction, and nabla derivative concept is defined as backward direction. Within the scope of this study, we consider the method of obtaining parameters of regression equation of integer values through time scale. Therefore, we implemented least squares method according to derivative definition of time scale and obtained coefficients related to the model. Here, there exist two coefficients originating from forward and backward jump operators relevant to the same model, which are different from each other. Occurrence of such a situation is equal to total number of values of vertical deviation between regression equations and observation values of forward and backward jump operators divided by two. We also estimated coefficients for the model using ordinary least squares method. As a result, we made an introduction to least squares method on time scale. We think that time scale theory would be a new vision in least square especially when assumptions of linear regression are violated.
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Dissertations / Theses on the topic "Ordinary least square"

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Ullah, Obaid. "The Effect of Remittances on Socio-Economic Condition and Decision Making Process of Rural Families : A Case Study of Peshawar Khyber Pukhunkhuwa Pakistan." Thesis, Södertörns högskola, Institutionen för samhällsvetenskaper, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-28199.

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The objective of the study is to analyze the effect of remittances on socio-economic conditions of rural families in Peshawar, and how remittances change the decision-making process of families. This study examines the effects of remittances on local population in three towns of Peshawar, i.e. Hayatabad, Faqir-Abad and Gulberg-area. The study is basically conducted to see how remittances bring changes in the life of the recipients. The research is quantitative, data was collected through questionnaires. For the research, a sample of 300 respondents was selected from three towns in Peshawar District. The results of the research were interpreted through statistical tools, regression model. The Ordinary least square method (OLS) was used to find out the effect of remittances on health sector and investment made by respondents in the form of purchased property and investment made in establishing their own businesses. Along with that, the simple Logit Model was also used. The result is generalized on linear model with link logit and binomial response. Findings stated that the literacy level of the emigrant’s household positively impacted on children’s probability to move to private education. The results reveals that the recipient invest 4% of their income on investment as a form of business and purchasing property while educated people appears not to be interested in investing money in businesses as they want to continue their jobs. Respondent are not using a large portion of their remittances for health perhaps mostly people are entitled to free services from the government. Remittances changed their standard of living and socio economic affairs of the remittances receiving respondents. According to my demographic information about respondents life, the remittances mostly brings changes in the physical part of people life such as Private Education, Personal transport, new houses, investment in buying properties, more electric appliances, bank balance etc., but culturally people are still conservative and believe in cultural values that have been practices by local population for centuries. Following are some main recommendations that this research has identified, Foreign remittances are improving the socio-economic conditions and decision making of rural families, however, their consumption behavior is not inclined towards investment, they rather prefer to enjoy luxurious household’s equipment. Therefore, it is recommended that these families should utilize their resources in more efficient way, and should go for short and long term investment avenues. Government must design policies in order to educate these families and create awareness among them that will enable them to look for sustainable domestic income, which would help the families in the long run. These families follow the norms and traditions, and they prefer sending their children abroad for earning purposes, which in turn is comparatively less profitable idea as compared to sending these children for higher education purpose.
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Li, Yang. "An Empirical Analysis of Family Cost of Children : A Comparison of Ordinary Least Square Regression and Quantile Regression." Thesis, Uppsala University, Department of Statistics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-126660.

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Quantile regression have its advantage properties comparing to the OLS model regression which are full measurement of the effects of a covariate on response, robustness and Equivariance property. In this paper, I use a survey data in Belgium and apply a linear model to see the advantage properites of quantile regression. And I use a quantile regression model with the raw data to analyze the different cost of family on different numbers of children and apply a Wald test. The result shows that for most of the family types and living standard, from the lower quantile to the upper quantile the family cost on children increases along with the increasing number of children and the cost of each child is the same. And we found a common behavior that the cost of the second child is significantly more than the cost of the first child for a nonworking type of family and all living standard families, at the upper quantile (from 0.75 quantile to 0.9 quantile) of the conditional distribution.

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Ntshobane, Gcobisa. "Capital structure and determinants of capital structure, before, during and after the 2008 financial crisis: A South African study." Master's thesis, Faculty of Commerce, 2021. http://hdl.handle.net/11427/33941.

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This study examines the effects of 2007/8 financial crisis on capital structure determinants of Johannesburg Stock Exchange (JSE) listed companies in South Africa. Data extracted from INET BFA Expert database was analyzed using regression models on the correlation between the leverage and company size, growth, profitability, tangibility, liquidity, non-debt tax shield along with Ordinary Least Squares based on the sample of JSE listed companies for the period of 2004 to 2013. The study examined two industries namely, Real estate and Retail industry. The results show that size, tangibility, profitability and liquidity have significant impact on the capital structure before, during and after financial crisis. Growth results were inconsistent over the period under review, and non-debt tax shield was found to be statistically insignificant. The study also shows that the 2007/8 had statistical significance on the capital structure of the listed companies in South Africa.
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Gaspard, Guetchine. "FLOOD LOSS ESTIMATE MODEL: RECASTING FLOOD DISASTER ASSESSMENT AND MITIGATION FOR HAITI, THE CASE OF GONAIVES." OpenSIUC, 2013. https://opensiuc.lib.siu.edu/theses/1236.

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This study aims at developing a model to estimate flood damage cost caused in Gonaives, Haiti by Hurricane Jeanne in 2004. In order to reach this goal, the influence of income, inundation duration and inundation depth, slope, population density and distance to major roads on the loss costs was investigated. Surveyed data were analyzed using Excel and ArcGIS 10 software. The ordinary least square and the geographically weighted regression analyses were used to predict flood damage costs. Then, the estimates were delineated using voronoi geostatistical map tool. As a result, the factors account for the costs as high as 83%. The flood damage cost in a household varies between 24,315 through 37,693 Haitian Gourdes (approximately 607.875 through 942.325 U.S. Dollars). Severe damages were spotted in the urban area and in the rural section of Bassin whereas very low and low losses are essentially found in Labranle. The urban area was more severely affected by comparison with the rural area. Damages in the urban area are estimated at 41,206,869.57USD against 698,222,174.10 17,455,554.35USD in the rural area. In the urban part, damages were more severe in Raboteau-Jubilée and in Downtown but Bigot-Parc Vincent had the highest overall damage cost estimated at 9,729,368.95 USD. The lowest cost 7,602,040.42USD was recorded in Raboteau. Approximately, 39.38% of the rural area underwent very low to moderate damages. Bassin was the most severely struck by the 2004 floods, but Bayonnais turned out to have the highest loss cost: 4,988,487.66 USD. Bassin along with Labranle had the least damage cost, 2,956,131.11 and 2,268,321.41 USD respectively. Based on the findings, we recommended the implementation and diversification of income-generating activities, the maintenance and improvement of drains, sewers and gullies cleaning and the establishment of conservation practices upstream of the watersheds. In addition, the model should be applied and validated using actual official records as reference data. Finally, the use of a calculation-based approach is suggested to determine flood damage costs in order to reduce subjectivity during surveys.
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Kronenberg, Kai. "ADVERTISING EFFECTIVENESS ON INTERNATIONAL TOURISM DEMAND IN ÅRE – AN ECONOMETRIC ANALYSIS." Thesis, Mittuniversitetet, Avdelningen för turismvetenskap och geografi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-19249.

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The objective of this study is to estimate advertising effects on international tourismdemand for the leading Swedish winter destination, Åre. The increasing share of foreigninbound tourists in this destination region creates a strong interest by shareholders toidentify the factors responsible for this trend. According to traditional micro-economictheory, economic factors, such as income and price, are considered as main determinantsfor tourism demand (Song and Witt 2000). However, according to advertising theories(Comanor and Wilson, 1974) and previous tourism research (Bhagwat and Debruine, 2008;Divisekera and Kulendran, 2006), this study additionally focuses on the brand awarenessof Åre as perceived by international tourists. More concretely, advertising theoriesdistinguish between the brand and the information function of advertising (Nelson, 1974).The former function follows the idea that advertising increases the level of productdifferentiation to build up a base of loyal customers. By contrast, the information functionimplies that advertising primarily provides information about products in order to increasethe market transparency. Accordingly, in order to estimate the impact of advertisingexpenditures for off- and online channels as well as promotional activities, furtherexplanatory variables, e.g. mega events, are considered in this study (Salman, 2003; Songet al., 2010). By applying ordinary least square (OLS) methods, demand elasticitycoefficients are estimated for each of the sending countries Norway, Finland, Russia,Denmark and the UK. Results show that advertising is the main significant driver oftourism demand from the UK, Russia and Finland, while a comparably weak advertisingleverage can be shown for Denmark and Norway. Interestingly, in contrast to microeconomictheories tested in previous research, income and tourism price levels reveal asbeing less significant drivers for demand in all analysed tourism markets. In turn, theresults provide evidence that the increased usage of online channels most significantlyaffects consumers’ buying behaviour. Finally, with respect to brand image perception,results reveal that the destination of Åre is perceived as a brand by tourists from Denmark.Moreover, for customers from the countries Norway and Finland, Åre indicates a weakbrand perception, while tourists from Russia and the UK don’t perceive Åre as a brand atall. The results gained by this research conducted at the level of the tourism destinationprovide useful hints about the factors influencing travel behaviour of tourists from maininternational markets. The study supports destination managers to appropriately adjustmarketing campaigns according to the predominant level of brand perception in respectivesending countries.
KK-Foundation project ‘Engineering the Knowledge Destination’ (no. 20100260; Stockholm, Sweden).
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Hu, Yajie. "Exploring Equity and Resilience of Transportation Network through Modeling Travel Behavior: A Study of OKI Region." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1554212469614412.

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Weng, Lichen. "A Hardware and Software Integrated Approach for Adaptive Thread Management in Multicore Multithreaded Microprocessors." FIU Digital Commons, 2012. http://digitalcommons.fiu.edu/etd/653.

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The Multicore Multithreaded Microprocessor maximizes parallelism on a chip for the optimal system performance, such that its popularity is growing rapidly in high-performance computing. It increases the complexity in resource distribution on a chip by leading it to two directions: isolation and unification. On one hand, multiple cores are implemented to deliver the computation and memory accessing resources to more than one thread at the same time. Nevertheless, it limits the threads’ access to resources in different cores, even if extensively demanded. On the other hand, simultaneous multithreaded architectures unify the domestic execu- tion resources together for concurrently running threads. In such an environment, threads are greatly affected by the inter-thread interference. Moreover, the impacts of the complicated distribution are enlarged by variation in workload behaviors. As a result, the microprocessor requires an adaptive management scheme to schedule threads throughout different cores and coordinate them within cores. In this study, an adaptive thread management scheme was proposed, integrating both hardware and software approaches. The instruction fetch policy at the hardware level took the responsibility by prioritizing domestic threads, while the Operating System scheduler at the software level was used to pair threads dynami- vi cally to multiple cores. The tie between them was the proposed online linear model, which was dynamically constructed for every thread based on data misses by the regression algorithm. Consequently, the hardware part of the proposed scheme proactively granted higher priority to the threads with less predicted long-latency loads, expecting they would better utilize the shared execution resources. Mean- while, the software part was invoked by such a model upon significant changes in the execution phases and paired threads with different demands to the same core to minimize competition on the chip. The proposed scheme was compared to its peer designs and overall 43% speedup was achieved by the integrated approach over the combination of two baseline policies in hardware and software, respectively. The overhead was examined carefully regarding power, area, storage and latency, as well as the relationship between the overhead and the performance.
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Peres, Ariádine. "Restrições ao crédito e o uso dos recursos financeiros nas empresas brasileiras." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2014. http://hdl.handle.net/10183/98311.

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Este estudo têm como objetivo identificar qual o comportamento de empresas brasileiras de capital aberto com relação à aplicação dos recursos financeiros de seus fluxos de caixa (recursos internos) em investimentos e não investimentos (em fins que não se configuram como um projeto real de investimento) no curto e longo prazo e mostrar como essa questão está relacionado com o grau de restrições financeiras enfrentado pelas empresas. Para alcançar esse objetivo foram estimadas quatro regressões pelo método OLS (Ordinary Least Square / Mínimos Quadrados Ordinários), cada uma delas com uma das variáveis resposta correspondentes aos principais usos de caixa, ou seja, retenção de caixa, investimentos, dividendos e redução do financiamento externo e com as variáveis explicativas dadas pelo fluxo de caixa nos períodos t, t-1 e t-2 e algumas variáveis de controle específicas da firma. Os resultados sugerem que empresas brasileiras restritas e irrestritas se comportam de forma diferente ao receberem um choque positivo em seus fluxos de caixa e que o comportamento das mesmas também difere no curto e no longo prazo. Empresas restritas e irrestritas ao receberem um choque positivo em seus fluxos de caixa, retêm caixa no período contemporâneo e alocam tais recursos intertemporalmente. Empresas restritas investem mais no curto prazo enquanto as irrestritas investem mais no longo prazo. No curto prazo, empresas irrestritas distribuem mais dividendos do que empresas irrestritas e no longo prazo, os coeficientes dos fluxos de caixa não são significativos para nenhum dos grupos. No curto prazo empresas irrestritas reduzem o financiamento externo, enquanto empresas restritas levantam mais financiamentos externos e no longo prazo, esse comportamento se inverte. Dessa forma, fica clara a importância de se considerar o longo prazo bem como as restrições financeiras enfrentadas pelas empresas.
This study aim to identify what is the behaviour of Brazilian public companies regarding the use of financial resources of cash flows (internal resources) in investments and not investments (for purposes that are not configured as a real investment project) in the short and long term and show how this is related to the degree of financial constraints faced by firms. To achieve this aim, four regressions were estimated by OLS ( Ordinary Least Square), each with one of the response variables corresponding to the main uses of cash, ie , cash holding, investments, dividends and external finance reduction and the explanatory variables given by the cash flow in periods t , t - 1 and t - 2 and some control variables specific of the firm. The results suggest that restricted and unrestricted Brazilian companies behave differently when they receive a positive shock on cash flows and their behavior also differs in the short and long term. When constrained and unconstrained firms receive a positive impact on cash flows, they retain cash in the contemporary period and intertemporally allocate such resources. Constrained firms invest more in the short term while the unrestricted invest more in the long run. In the short term, unconstrained firms distribute more dividends than unconstrained firms and in the long run, the coefficients of cash flows are not significant for either groups. In the short term unconstrained firms reduce external finance, while constrained firms raise more external finance and in the long term, this behavior is reversed. Thus, it is clear that it matters to consider the long term as well as financial constraints faced by firms.
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Larrabee, Beth R. "Ordinary least squares regression of ordered categorical data: inferential implications for practice." Kansas State University, 2011. http://hdl.handle.net/2097/8850.

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Master of Science
Department of Statistics
Nora Bello
Ordered categorical responses are frequently encountered in many disciplines. Examples of interest in agriculture include quality assessments, such as for soil or food products, and evaluation of lesion severity, such as teat ends status in dairy cattle. Ordered categorical responses are characterized by multiple categories or levels recorded on a ranked scale that, while apprising relative order, are not informative of magnitude of or proportionality between levels. A number of statistically sound models for ordered categorical responses have been proposed, such as logistic regression and probit models, but these are commonly underutilized in practice. Instead, the ordinary least squares linear regression model is often employed with ordered categorical responses despite violation of basic model assumptions. In this study, the inferential implications of this approach are investigated using a simulation study that evaluates robustness based on realized Type I error rate and statistical power. The design of the simulation study is motivated by applied research cases reported in the literature. A variety of plausible scenarios were considered for simulation, including various shapes of the frequency distribution and different number of categories of the ordered categorical response. Using a real dataset on frequency of antimicrobial use in feedlots, I demonstrate the inferential performance of ordinary least squares linear regression on ordered categorical responses relative to a probit model.
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Santos, Levi Alã Neves dos. "Mínimos quadrados ordinários (MQO) na produção científica brasileira: a interdisciplinaridade entre a econometria e as metrias da informação (bibliometria, informetria e cientometria)." Universidade Federal da Bahia, 2017. http://repositorio.ufba.br/ri/handle/ri/25329.

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Analisa a produção científica brasileira (artigos nacionais, artigos internacionais, anais de eventos e livros) através dos Mínimos Quadrados Ordinários (MQO). Para tanto, discorre sobre o percurso histórico e de aplicação das metrias que a Ciência da Informação (CI) vem construindo, desde a mais primordial de todas, a bibliometria, oriunda da biblioteconomia, passando pelas visões modernas como a cienciometria até a informetria. Explica como a econometria constrói o seu modelo de análise, que é utilizado para pesquisas na economia e, ao mesmo tempo, reflete como esse método pode ser trazido para as metrias da informação. Explica e expõe o método de estimação por MQO para a análise de regressão, que é a proposta desta tese. Pesquisa aplicada descritiva com abordagem quantitativa com procedimentos baseados no tipo de pesquisa estudo de caso do levantamento de dados a partir do Portal do Plano Tabular do CNPq do ano de 2010. Os critérios para delineamento da pesquisa foram aprofundados, na revisão de literatura, em referências tanto da área da CI quanto da bibliometria, estatística e econometria. Este estudo, metodologicamente, conta com a abordagem conceitual da bibliometria e da CI em busca de teorias aplicáveis aos estudos em MQO e a aplicação empírica do MQO se aproxima da concepção econométrica. A tese conclui que a utilização de técnicas de análises das funções de regressão construída por meio de MQO possibilita a criação de um modelo de previsão da produção científica brasileira. Esse modelo é construído a partir da correlação e determinação detectada entre o número de doutores e a produção científica destes em cada estado do Brasil. Com a aplicação de estratégias econométricas (índice de correlação, índice de determinação, forma funcional de curva de regressão e cálculo dos parâmetros da função por MQO), foi possível construir um modelo de previsão.
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Books on the topic "Ordinary least square"

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Halperin, Sandra, and Oliver Heath. 16. Patterns of Association. Oxford University Press, 2017. http://dx.doi.org/10.1093/hepl/9780198702740.003.0016.

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This chapter discusses the principles of bivariate analysis as a tool for helping researchers get to know their data and identify patterns of association between two variables. Bivariate analysis offers a way of establishing whether or not there is a relationship between two variables, a dependent variable and an independent variable. With bivariate analysis, theoretical expectations can be compared against evidence from the real world to see if the theory is supported by what is observed. The chapter examines the pattern of association between dependent and independent variables, with particular emphasis on hypothesis testing and significance tests. It discusses ordinary least squares (OLS) regression and cross-tabulation, two of the most widely used statistical analysis techniques in political research. Finally, it explains how to state the null hypothesis, calculate the chi square, and establishing the correlation between the dependent and independent variables.
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Walsh, Bruce, and Michael Lynch. Analysis of Short-term Selection Experiments: 1. Least-squares Approaches. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.003.0018.

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This chapter examines short-term (a few generations) selection response in the mean of a trait. Traditionally, such experiments are analyzed using least-squares (LS) approaches. While ordinary LS (OLS) is often used, genetic drift causes the residual to be both correlated and heteroscedastic, resulting in the sampling variances given by OLS being too small. This chapter details the appropriate general LS (GLS) approaches to properly account for this residual error structure. It also reviews some of the common features observed in short-term selection experiments and examines experimental designs, such as the use of a control population versus a divergence-selection approach. It concludes by discussing another linear model used mainly by plant breeders, generation-means analysis (GMA), wherein remnant seed for several generations of response are crossed and then grown in a common garden. Such an analysis can provide insight into the genetic nature of any response.
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Witkov, Carey, and Keith Zengel. Chi-Squared Data Analysis and Model Testing for Beginners. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198847144.001.0001.

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This book is the first to make chi-squared model testing, one of the data analysis methods used to discover the Higgs boson and gravitational waves, accessible to undergraduate students in introductory physics laboratory courses. By including uncertainties in the curve fitting, chi-squared data analysis improves on the centuries old ordinary least squares and linear regression methods and combines best fit parameter estimation and model testing in one method. A toolkit of essential statistical and experimental concepts is developed from the ground up with novel features to interest even those familiar with the material. The presentation of one- and two-parameter chi-squared model testing, requiring only elementary probability and algebra, is followed by case studies that apply the methods to simple introductory physics lab experiments. More challenging topics, requiring calculus, are addressed in an advanced topics chapter. This self-contained and student-friendly introduction to chi-squared analysis and model testing includes a glossary, end-of-chapter problems with complete solutions, and software scripts written in several popular programming languages, that the reader can use for chi-squared model testing. In addition to introductory physics lab students, this accessible introduction to chi-squared analysis and model testing will be of interest to all who need to learn chi-squared model testing, e.g. beginning researchers in astrophysics and particle physics, beginners in data science, and lab students in other experimental sciences.
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Cooray, Arusha, Krishna Chaitanya Vadlamannati, and Indra de Soysa. Do bigger health budgets cushion pandemics? An empirical test of COVID-19 deaths across the world. UNU-WIDER, 2020. http://dx.doi.org/10.35188/unu-wider/2020/922-8.

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How has government healthcare spending prepared countries for tackling the COVID-19 pandemic? Arguably, spending is the primary policy tool of governments in providing effective health. We argue that the effectiveness of spending in reducing COVID deaths is conditional on the existence of healthcare equity and lower political corruption, because the health sector is particularly susceptible to political spending. Our results, obtained using ordinary least squares (OLS) and two-stage least squares (2SLS) estimation, suggest that higher spending targeted at reducing inequitable access to health has reduced COVID deaths. Consistent with the findings of others, our results indirectly suggest that health spending is necessary, but not sufficient unless accompanied by building resilience against the spread of deadly disease. Equitable health systems ease the effects of COVID presumably because they allow states to reach and treat people. Spending aimed at increasing health system capacity by increasing access thus seems a sound strategy for fighting the spread of disease, ultimately benefiting us all.
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Kritz, Mary M., and Douglas T. Gurak. International Student Mobility. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198815273.003.0011.

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This chapter examines the role that sending country structural factors play in influencing the proportion of tertiary students studying abroad. It examines how outbound mobility ratio (OMR) responds to sending county supply and demand for tertiary education, population size, per capital GDP, development, education expenditures, and other factors. In all Ordinary Least Squares (OLS) and fixed-effect model specifications, the OMR had a negative relationship to tertiary supply. While countries with larger populations send more students abroad, they have smaller OMRs. Fixed-effects models also showed that changes in tertiary supply and the percentage of GDP spent on tertiary education were negatively related to OMRs. The chapter reviews government scholarship programmes sponsored by Global South countries and the practices they pursue to encourage student return and strengthen tertiary capacity in science, technology, engineering, and mathematics (STEM). These programmes in developing countries in Africa, Asia, and Latin America are changing international student flows.
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Brazier, John, Julie Ratcliffe, Joshua A. Salomon, and Aki Tsuchiya. Modelling health state valuation data. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198725923.003.0005.

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This chapter examines the technical issues in modelling health state valuation data. Most measures of health define too many states to directly value all of them (e.g. SF-6D defines 18,000 health states). The solution has been to value a subset and by using modelling to predict the values of all states. This chapter reviews two approaches to modelling: one using multiattribute utility theory to determine health values given an assumed functional form; and the other is using statistical modelling of SF-6D preference data that are skewed, bimodal, and clustered by respondents. This chapter examines the selection of health states for valuation, data preparation, model specification, and techniques for modelling the data starting with ordinary least squares (OLS) and moving on to more complex techniques including Bayesian non-parametric and semi-parametric approaches, and a hybrid approach that combines cardinal preference data with the results of paired data from a discrete choice experiment.
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Li, Quan. Using R for Data Analysis in Social Sciences. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190656218.001.0001.

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This book seeks to teach undergraduate and graduate students in social sciences how to use R to manage, visualize, and analyze data in order to answer substantive questions and replicate published findings. This book distinguishes itself from other introductory R or statistics books in three ways. First, targeting an audience rarely exposed to statistical programming, it adopts a minimalist approach and covers only the most important functions and skills in R that one will need for conducting reproducible research projects. Second, it emphasizes meeting the practical needs of students using R in research projects. Specifically, it teaches students how to import, inspect, and manage data; understand the logic of statistical inference; visualize data and findings via histograms, boxplots, scatterplots, and diagnostic plots; and analyze data using one-sample t-test, difference-of-means test, covariance, correlation, ordinary least squares (OLS) regression, and model assumption diagnostics. Third, it teaches students how to replicate the findings in published journal articles and diagnose model assumption violations. The principle behind this book is to teach students to learn as little R as possible but to do as much reproducible, substance-driven data analysis at the beginner or intermediate level as possible. The minimalist approach dramatically reduces the learning cost but still proves adequate information for meeting the practical research needs of senior undergraduate and beginning graduate students. Having completed this book, students can use R and statistical analysis to answer questions regarding some substantively interesting continuous outcome variable in a cross-sectional design.
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Book chapters on the topic "Ordinary least square"

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Wooditch, Alese, Nicole J. Johnson, Reka Solymosi, Juanjo Medina Ariza, and Samuel Langton. "Ordinary Least Squares Regression." In A Beginner’s Guide to Statistics for Criminology and Criminal Justice Using R, 245–68. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-50625-4_15.

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Malley, James D. "The Ordinary Least Squares Estimates." In Optimal Unbiased Estimation of Variance Components, 29–35. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4615-7554-2_4.

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Praag, M. S. "Probit Ordinary Least Squares (POLS)." In Encyclopedia of Quality of Life and Well-Being Research, 5072–73. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_3328.

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Praag, M. S. Van B. "Cardinal Ordinary Least Squares (COLS)." In Encyclopedia of Quality of Life and Well-Being Research, 536–37. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_3329.

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Zdaniuk, Bozena. "Ordinary Least-Squares (OLS) Model." In Encyclopedia of Quality of Life and Well-Being Research, 4515–17. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_2008.

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Schuberth, Florian, and Gabriele Cantaluppi. "Ordinal Consistent Partial Least Squares." In Partial Least Squares Path Modeling, 109–50. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64069-3_6.

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Balzer, W., and E. W. Haendler. "Ordinary Least Squares as a Method of Measurement." In Philosophy of Economics, 129–46. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-2319-5_8.

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Cantaluppi, Gabriele, and Giuseppe Boari. "A Partial Least Squares Algorithm Handling Ordinal Variables." In Springer Proceedings in Mathematics & Statistics, 295–306. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40643-5_22.

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Srijith, P. K., Shirish Shevade, and S. Sundararajan. "A Probabilistic Least Squares Approach to Ordinal Regression." In Lecture Notes in Computer Science, 683–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35101-3_58.

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Krämer, Walter. "Asymptotic Equivalence of Ordinary Least Squares and Generalized Least Squares with Trending Regressors and Stationary Autoregressive Disturbances." In Econometrics in Theory and Practice, 137–42. Heidelberg: Physica-Verlag HD, 1998. http://dx.doi.org/10.1007/978-3-642-47027-1_13.

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Conference papers on the topic "Ordinary least square"

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Harun, Suriyati, Yasmin Yahya, Nurashikin Saaludin, and Wan Suriyani Che Wan Ahmad. "Comparison of ordinary least square and mixed-effect regression models for estimation of tree diameter increment." In IMCOM '15: The 9th International Conference on Ubiquitous Information Management and Communication. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2701126.2701167.

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Liu, Jingdong, Won-Ho Choi, and Fei Hao. "Research on the Influencing Factors of Film Box Office Based on Ordinary Least Square and Threshold Quantile Autoregressive Model." In 2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS). IEEE, 2019. http://dx.doi.org/10.1109/iucc/dsci/smartcns.2019.00065.

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Hays, Joe, Adrian Sandu, Corina Sandu, and Dennis Hong. "Parametric Design Optimization of Uncertain Ordinary Differential Equation Systems." In ASME 2011 International Mechanical Engineering Congress and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/imece2011-62789.

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This work presents a novel optimal design framework that treats uncertain dynamical systems described by ordinary differential equations. Uncertainty in multibody dynamical systems comes from various sources, such as: system parameters, initial conditions, sensor and actuator noise, and external forcing. The inclusion of uncertainty in design is of paramount practical importance because all real-life systems are affected by it. Designs that ignore uncertainty often lead to poor robustness and suboptimal performance. In this work uncertainties are modeled using Generalized Polynomial Chaos and are solved quantitatively using a least-square collocation method. The uncertainty statistics are explicitly included in the optimization process. Systems that are nonlinear, have active constraints, or opposing design objectives are shown to benefit from the new framework. Specifically, using a constraint-based multi-objective formulation, the direct treatment of uncertainties during the optimization process is shown to shift, or off-set, the resulting Pareto optimal trade-off curve. A nonlinear vehicle suspension design problem, subject to parametric uncertainty, illustrates the capability of the new framework to produce an optimal design that accounts for the entire family of systems within the associated probability space.
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Siami, A., and M. Farid. "Identification and Defect Detection of Continuous Dynamic Systems." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-14364.

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This paper presents a systematic and efficient algorithm using a coupled finite element - finite difference - least square method for identification and defect detection of continuous system using dynamic response of such systems. First the governing partial differential equations of motion of continuous systems such as beams are reduced to a set of ordinary differential equations in time domain using finite elements. Then finite difference method is used to convert these equations into a set of algebraic equations. This set of equations is considered as a set of equality constraints of an optimization problem in which the objective function is the summation of the squares of differences between measured data at specific points and the predicted data obtained by the solution of the governing system of differential of equations. This method has been successfully applied to find mechanical properties of aforementioned systems in an iterative procedure.
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Chen, De-Qi, Liang-Ming Pan, and De-Wen Yuan. "Experimental Investigation of Saturated Flow Boiling Heat Transfer of Vertical Narrow Rectangular Channel." In 16th International Conference on Nuclear Engineering. ASMEDC, 2008. http://dx.doi.org/10.1115/icone16-48532.

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Narrow rectangular channel has been widely used at evaporator of cryogenic engineering and electronics cooling. At present paper, saturated flow boiling heat transfer at vertical narrow rectangular channel with gaps of 1.0, 1.5 and 2.5 was experimentally investigated, the heat transfer characteristics at various operating conditions were tested and discussed, and the correlation of saturated boiling heat transfer coefficient was regressed used Least Square Method according to experimental results. It shows that heat transfer coefficient decreases at wider gaps and higher inlet pressure, and it increases at higher flow rate, heat flux and increased vapor quality. Compared with traditional correlation for ordinary channel, the discrepancy is significant. Considering the size effects, a new correlation was proposed to estimate the heat transfer coefficient. The error of the regressed correlation is within ±12%.
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Tu, Ying, Michael Muskulus, and Thorvald C. Grindstad. "Two Methods for the Inverse Estimation of Local Slamming Loads on a Jacket Structure." In ASME 2016 35th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/omae2016-54462.

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This article illustrates two inverse methods to estimate the local slamming forces on a jacket structure. The experimental data from the hammer test and the wave test are used as the inputs. One method uses two deconvolution techniques: a conjugate gradient technique to solve the impulse response functions and a weighted eigenvector expansion technique to reconstruct the wave impact forces. The other method uses linear regression with the ordinary least square technique to estimate the wave impact forces. The results calculated with these two different methods are highly identical, which enhances the confidence in the result accuracy. The time series of the reconstructed forces are detailed at a millisecond level, which provides decent information on the shape of the forces. This capability enables the methods to be a very useful tool for the further investigations of the local slamming forces.
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Kaban, Ata. "A New Look at Compressed Ordinary Least Squares." In 2013 IEEE 13th International Conference on Data Mining Workshops (ICDMW). IEEE, 2013. http://dx.doi.org/10.1109/icdmw.2013.152.

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Chavat, J. P., and S. Nesmachnow. "Data analysis approach for characterizing residential energy consumption based on statistics of household appliances ownership." In 1st International Workshop on Advanced Information and Computation Technologies and Systems 2020. Crossref, 2021. http://dx.doi.org/10.47350/aicts.2020.02.

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Worldwide, residential electricity demand has increased constantly, expecting to double in 2050 the demand of 2010. Different policies have been proposed to achieve a smart use of electricity. This article presents a data-analysis approach to evaluate the potential household electricity consumption from statistical data. The main axis of the study are statistics of appliance ownership and information of the appliance characteristics, gathered from census surveys and local shops. An index to estimate the electricity consumption is performed. The validation of the proposed index is carried out using real consumption data from the Electricity Consumption Data set of Uruguay and Ordinary Least Square linear regressions. Jupyter notebooks, Python language and well-know libraries such as Pandas and Numpy were used during the implementation. The main results show that administrative regions located on the West/Southwest coastlines present the highest index scores. In turn, census sections/segments on the West/Southwest coastlines of Montevideo performed the highest scores while the lowest scores can be found at the outskirts of the city. The proposed methodology can be applied for electricity consumption estimation in other regions/countries where census data is publicly available.
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Arshad, Saher, Saima Qamar, Tayba Jabbar, and Ahsan Malik. "Parameter estimation of a DC motor using ordinary least squares and recursive least squares algorithms." In the 8th International Conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1943628.1943659.

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Gieseke, Fabian, Kai Lars Polsterer, Ashish Mahabal, Christian Igel, and Tom Heskes. "Massively-parallel best subset selection for ordinary least-squares regression." In 2017 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2017. http://dx.doi.org/10.1109/ssci.2017.8285225.

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Reports on the topic "Ordinary least square"

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Cumby, Robert, and John Huizinga. Testing The Autocorrelation Structure of Disturbances in Ordinary Least Squares and Instrumental Variables Regressions. Cambridge, MA: National Bureau of Economic Research, October 1990. http://dx.doi.org/10.3386/t0092.

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Chervenkov, Hristo, and Kiril Slavov. Theil–Sen Estimator vs. Ordinary Least Squares — Trend Analysis for Selected ETCCDI Climate Indices. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, February 2018. http://dx.doi.org/10.7546/crabs.2019.01.06.

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Tiruneh, Dawit T., John Hoddinott, Caine Rolleston, Ricardo Sabates, and Tassew Woldehanna. Understanding Achievement in Numeracy Among Primary School Children in Ethiopia: Evidence from RISE Ethiopia Study. Research on Improving Systems of Education (RISE), May 2021. http://dx.doi.org/10.35489/bsg-rise-wp_2021/071.

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Ethiopia has succeeded in rapidly expanding access to primary education over the past two decades. However, learning outcomes remain low among primary school children and particularly among girls and children from disadvantaged backgrounds. Starting with a systematic review of quantitative studies on the determinants of learning outcomes among primary school children in Ethiopia, this study then examined key determinants of students’ numeracy achievement over the 2018-19 school year. The study focused on Grade 4 children (N=3,353) who are part of an on-going longitudinal study. The two questions that guided this study are: what are the key determinants of numeracy achievement at Grade 4 in primary schools in Ethiopia, and how does our current empirical study contribute to understanding achievement differences in numeracy among primary school children in Ethiopia? We employed descriptive and inferential statistics to examine factors that determine differences in numeracy scores at the start and end of the school year, as well as determinants of numeracy scores at the end of the school year conditional on achievement at the start of the school year. We examined differences across gender, region, and rural-urban localities. We also used ordinary least squares and school ‘fixed effects’ approaches to estimate the key child, household and school characteristics that determine numeracy scores in Grade 4. The findings revealed that boys significantly outperformed girls in numeracy both at the start and end of the 2018/19 school year, but the progress in numeracy scores over the school year by boys was similar to that of girls. Besides, students in urban localities made a slightly higher progress in numeracy over the school year compared to their rural counterparts. Students from some regions (e.g., Oromia) demonstrated higher progress in numeracy over the school year relative to students in other regions (e.g., Addis Ababa). Key child (e.g., age, health, hours spent per day studying at home) and school- and teacher-related characteristics (e.g., provision of one textbook per subject for each student, urban-rural school location, and teachers’ mathematics content knowledge) were found to be significantly associated with student progress in numeracy test scores over the school year. These findings are discussed based on the reviewed evidence from the quantitative studies in Ethiopia.
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