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Relevant bibliographies by topics / Serial correlation coefficient

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Academic literature on the topic 'Serial correlation coefficient'

Author: Grafiati

Published: 4 June 2021

Last updated: 5 February 2022

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Journal articles on the topic "Serial correlation coefficient"

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Provost, Serge B., and Edmund M. Rudiuk. "The Sampling Distribution of the Serial Correlation Coefficient." American Journal of Mathematical and Management Sciences 15, no. 1-2 (1995): 57–81. http://dx.doi.org/10.1080/01966324.1995.10737387.

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Yue, S., and C. Y. Wang. "The null distribution of sample serial correlation coefficient." Stochastic Environmental Research and Risk Assessment (SERRA) 16, no. 1 (2002): 77–100. http://dx.doi.org/10.1007/s00477-001-0086-9.

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Stanford, D. A., and B. Pagurek. "On the serial correlation for number in system in the stationary GI/M/1 bulk arrival and GI/Em/1 queues." Journal of Applied Probability 29, no. 2 (1992): 404–17. http://dx.doi.org/10.2307/3214577.

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The generating functions for the serial covariances for number in system in the stationary GI/M/1 bulk arrival queue with fixed bulk sizes, and the GI/Em/1 queue, are derived. Expressions for the infinite sum of the serial correlation coefficients are also presented, as well as the first serial correlation coefficient in the case of the bulk arrival queue. Several numerical examples are considered.

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Stanford, D. A., and B. Pagurek. "On the serial correlation for number in system in the stationary GI/M/1 bulk arrival and GI/Em /1 queues." Journal of Applied Probability 29, no. 02 (1992): 404–17. http://dx.doi.org/10.1017/s0021900200043151.

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The generating functions for the serial covariances for number in system in the stationary GI/M/1 bulk arrival queue with fixed bulk sizes, and the GI/Em /1 queue, are derived. Expressions for the infinite sum of the serial correlation coefficients are also presented, as well as the first serial correlation coefficient in the case of the bulk arrival queue. Several numerical examples are considered.

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Hu, Xuemei, Zhizhong Wang, and Feng Liu. "Testing Serial Correlation in Semiparametric Varying-Coefficient Partially Linear Models." Communications in Statistics - Theory and Methods 38, no. 13 (2009): 2145–63. http://dx.doi.org/10.1080/03610920802491766.

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Field, Chris, and John Robinson. "Relative errors for bootstrap approximations of the serial correlation coefficient." Annals of Statistics 41, no. 2 (2013): 1035–53. http://dx.doi.org/10.1214/13-aos1111.

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Hu, Xue-mei, Zhi-zhong Wang, and Feng Liu. "Testing serial correlation in semiparametric varying-coefficient partially linear EV models." Acta Mathematicae Applicatae Sinica, English Series 24, no. 1 (2008): 99–116. http://dx.doi.org/10.1007/s10255-006-6168-1.

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Schubert, Emery. "Correlation analysis of continuous emotional response to music: Correcting for the effects of serial correlation." Musicae Scientiae 5, no. 1_suppl (2001): 213–36. http://dx.doi.org/10.1177/10298649020050s108.

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Publications of research concerning continuous emotional responses to music are increasing. The developing interest brings with it a need to understand the problems associated with the analysis of time series data. This article investigates growing concern in the use of conventional Pearson correlations for comparing time series data. Using continuous data collected in response to selected pieces of music, with two emotional dimensions for each piece, two falsification studies were conducted. The first study consisted of a factor analysis of the individual responses using the original data set

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Vanhonacker, Wilfried R. "Estimating an Autoregressive Current Effects Model of Sales Response when Observations are Aggregated over Time: Least Squares versus Maximum Likelihood." Journal of Marketing Research 25, no. 3 (1988): 301–7. http://dx.doi.org/10.1177/002224378802500308.

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Estimating autoregressive current effects models is not straightforward when observations are aggregated over time. The author evaluates a familiar iterative generalized least squares (IGLS) approach and contrasts it to a maximum likelihood (ML) approach. Analytic and numerical results suggest that (1) IGLS and ML provide good estimates for the response parameters in instances of positive serial correlation, (2) ML provides superior (in mean squared error) estimates for the serial correlation coefficient, and (3) IGLS might have difficulty in deriving parameter estimates in instances of negati

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Chen, Jia, Degui Li, and Yingcun Xia. "Estimation of a rank-reduced functional-coefficient panel data model with serial correlation." Journal of Multivariate Analysis 173 (September 2019): 456–79. http://dx.doi.org/10.1016/j.jmva.2019.04.005.

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Dissertations / Theses on the topic "Serial correlation coefficient"

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Blankenburg, Sven. "Theoretical mechanisms of information filtering in stochastic single neuron models." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät, 2016. http://dx.doi.org/10.18452/17577.

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Die vorliegende Arbeit beschäftigt sich mit Mechanismen, die in Einzelzellmodellen zu einer frequenzabhängigen Informationsübertragung führen können. Um dies zu untersuchen, werden Methoden aus der theoretischen Physik (Statistische Physik) und der Informationstheorie angewandt. Die Informationsfilterung in mehreren stochastischen Neuronmodellen, in denen unterschiedliche Mechanismen zur Informationsfilterung führen können, werden numerisch und, falls möglich, analytisch untersucht. Die Bandbreite der betrachteten Modelle erstreckt sich von reduzierten strombasierten ’Integrate-and-Fire’ (IF)

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Schwalger, Tilo. "The interspike-interval statistics of non-renewal neuron models." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2013. http://dx.doi.org/10.18452/16824.

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Um die komplexe Dynamik von Neuronen und deren Informationsverarbeitung mittels Pulssequenzen zu verstehen, ist es wichtig, die stationäre Puls-Aktivität zu charakterisieren. Die statistischen Eigenschaften von Pulssequenzen können durch vereinfachte stochastische Neuronenmodelle verstanden werden. Eine gut ausgearbeitete Theorie existiert für die Klasse der Erneuerungsmodelle, welche die statistische Unabhängigkeit der Interspike-Intervalle (ISI) annimmt. Experimente haben jedoch gezeigt, dass viele Neuronen Korrelationen zwischen ISIs aufweisen und daher nicht gut durch einen Erneue

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Fu, Tsung-Chiang, and 傅宗襁. "Estimation of rank correlation coefficient for two serial gap times in the presence of induced informative censoring." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/86094025504589048844.

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碩士<br>國立臺灣大學<br>流行病學研究所<br>97<br>In follow-up studies, bivariate event data are often encountered when subjects may experience two events with different or the same types. In analyzing bivariate event data, two types of time scale are considered in the literature: the times to events and the times between adjacent events. When the occurrence of during follow-up two events is in a chronological order, the gap time, defined as the time between adjacent events, is often of interest in the study. In the literature, measures of association between bivariate event times have been studied, but not ye

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Books on the topic "Serial correlation coefficient"

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Dufour, Jean-Marie. Distribution-free bounds for serial correlation coefficients in heteroskedastic symmetric time series. Centre interuniversitaire de recherche en économie quantitative, 2005.

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Davis, Lori Ann. estimating random effects and serial correlation in random coefficient models: To weight or not to weight. 2002.

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Ross, John, Igor Schreiber, and Marcel O. Vlad. Determination of Complex Reaction Mechanisms. Oxford University Press, 2006. http://dx.doi.org/10.1093/oso/9780195178685.001.0001.

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In a chemical system with many chemical species several questions can be asked: what species react with other species: in what temporal order: and with what results? These questions have been asked for over one hundred years about simple and complex chemical systems, and the answers constitute the macroscopic reaction mechanism. In Determination of Complex Reaction Mechanisms authors John Ross, Igor Schreiber, and Marcel Vlad present several systematic approaches for obtaining information on the causal connectivity of chemical species, on correlations of chemical species, on the reaction pathw

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Book chapters on the topic "Serial correlation coefficient"

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Yitzhaki, Shlomo, and Edna Schechtman. "The Gini Equivalents of the Covariance, the Correlation, and the Regression Coefficient." In Springer Series in Statistics. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-4720-7_3.

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Höffding, Wassily. "On the Distribution of the Rank Correlation Coefficient τ When the Variates are not Independent." In Springer Series in Statistics. Springer New York, 1994. http://dx.doi.org/10.1007/978-1-4612-0865-5_7.

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"Correlation Coefficients." In Wiley Series in Probability and Statistics. John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9780470539873.ch4.

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"Chapter I0: Canonical correlation coefficients." In Institute of Mathematical Statistics Lecture Notes - Monograph Series. Institute of Mathematical Statistics, 2007. http://dx.doi.org/10.1214/lnms/1196285116.

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"Distribution of the Sample Multiple Correlation Coefficient." In Statistics: A Series of Textbooks and Monographs. Chapman and Hall/CRC, 2006. http://dx.doi.org/10.1201/9781420011371.ch36.

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Drasovean, Romana, and Gabriel Murariu. "Water Quality Parameters and Monitoring Soft Surface Water Quality Using Statistical Approaches." In Wastewater Treatment [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.97372.

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Water is the matrix of life and is indispensable on Earth. Water has a multitude of applications and all known life forms depend on it. Therefore, water quality is important for all of us. Water quality can be represented by a set of physical, chemical, biological and bacteriological characteristics. These parameters allow water to be classified in multiple categories leading to its use for a specific purpose. This chapter establishes the connections between external causes and their effect on water quality parameters. In order to provide information on water quality, different Water Quality Index (WQI) models can be used. In order to study the association between water quality parameters, several correlation coefficients have been developed. For a coherent statistical approach, we have used Pearson and Spearman correlations. In order to exemplify the manner in which WQI can be calculated and interpreted, we used a series of data from our previous work, consisting of 13 parameters measured for water samples taken from the Danube River, from Galati City area, Romania.

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Smith, Gary. "If You Torture the Data Long Enough." In The AI Delusion. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198824305.003.0008.

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I recently received an e-mail that offered me a way to automate my research: Dear Professor Smith, We would like to introduce you to [our] brand new research tool . . . , ready to automate your empirical research basing on official statistical time series databases. [Our software] has been designed to explore and discover new exciting economic correlations directly from your desktop. No extra software required, no need to crawl thousands of databases manually. You’ll be up and running in no time your first big data project. The e-mail went on to boast that their software will calculate “correlation coefficients with millions of statistical time series,” “identify unexpected interdependences,” and “find new insights.” The creative grammar was one thing. More disheartening was their assumption that I wanted to sift through literally trillions of correlations looking for unexpected patterns. An unexpected pattern has no logical basis—and I am skeptical of patterns that defy logic. Statistical tests assume that researchers have well-defined theories in mind and gather appropriate data to test their theories. This company assumed that I was eager and willing to pay a substantial amount of money to work the other way around. Look at every possible correlation—not caring whether they made sense or not—and report the correlations that turn out to be the most statistically persuasive. It is a sign of the times, but not an inspiring sign. Many important scientific theories started out as efforts to explain observed patterns. For example, during the 1800s,most biologists believed that parental characteristics were averaged together to determine the characteristics of their offspring. For example, a child’s height is an average of the father’s and mother’s heights, modified by environmental influences. However, Gregor Mendel discovered something quite different in his experiments with pea plants. Mendel was born in Austria in 1822 and grew up on his family’s farm. His parents expected him to take over the farm, but Mendel was an excellent student and became an Augustinian monk at a monastery known for its scientific library and research. Perhaps because of his farming roots, Mendel conducted meticulous studies of tens of thousands of pea plants grown in the monastery’s gardens over an eight-year period.

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Pabreja, Kavita. "Artificial Neural Network for Markov Chaining of Rainfall Over India." In Research Anthology on Artificial Neural Network Applications. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-2408-7.ch053.

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Rainfall forecasting plays a significant role in water management for agriculture in a country like India where the economy depends heavily upon agriculture. In this paper, a feed forward artificial neural network (ANN) and a multiple linear regression model has been utilized for lagged time series data of monthly rainfall. The data for 23 years from 1990 to 2012 over Indian region has been used in this study. Convincing values of root mean squared error between actual monthly rainfall and that predicted by ANN has been found. It has been found that during monsoon months, rainfall of every n+3rd month can be predicted using last three months' (n, n+1, n+2) rainfall data with an excellent correlation coefficient that is more than 0.9 between actual and predicted rainfall. The probabilities of dry seasonal month, wet seasonal month for monsoon and non-monsoon months have been found.

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Sposito, Garrison. "The Statistical Physics of Subsurface Solute Transport." In Vadose Zone Hydrology. Oxford University Press, 1999. http://dx.doi.org/10.1093/oso/9780195109900.003.0007.

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The first detailed study of solute movement through the vadose zone at field scales of space and time was performed by Biggar and Nielsen (1976). Their experiment was conducted on a 150-ha agricultural site located at the West Side Field Station of the University of California, where the soil (Panoche series) exhibits a broad range of textures. Twenty well-separated, 6.5-m-square plots, previously instrumented to monitor matric potential and withdraw soil solution for chemical analysis, were ponded with water containing low concentrations of the tracer anions chloride and nitrate. After about 1 week, steady-state infiltration conditions were established, and 0.075 m of water containing the two anions at concentrations between 0.1 and 0.2 mol L-1 was leached through each plot at the local infiltration rate, which varied widely from 0.054 to 0.46 m day-1, depending on plot location. Once this solute pulse had infiltrated (< 1.5 days), leaching under ponded conditions was recommenced with the water low in chloride and nitrate. Solution samples were extracted before and after the solute pulse input at six depths up to 1.83 m below the land surface in each plot. Analyses of these samples for chloride and nitrate produced a broad range of concentration data which nonetheless showed an excellent linear correlation between the concentrations of the two anions (R2= 0.975), with a proportionality coefficient equal to that expected on the basis of the composition of the input pulse. Values of the measured solute concentrations at each sampling depth were tabulated as functions of the leaching time. Biggar and Nielsen (1976) decided to fit their very large concentration-depth-time database to a finite-pulsc-input solution of the one-dimensional advection-dispersion equation, leaving both the dispersion coefficient D and advection velocity u as adjustable parameters. The 359 field-wide values of u obtained in this way were highly variable (CV ≈ 200%), but also highly correlated (R2 = 0.84) and proportional to values of the advection velocity calculated directly as the ratio of water flux density to water content in each field plot (Biggar and Nielsen, 1976, figure 4).

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Tuck, Adrian F. "Temperature Intermittency and Ozone Photodissociation." In Atmospheric Turbulence. Oxford University Press, 2008. http://dx.doi.org/10.1093/oso/9780199236534.003.0008.

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During the last two missions performed by the ER-2 in the Arctic lower stratosphere, POLARIS in the summer of 1997 and SOLVE during the winter of 1999–2000, an unexpected correlation emerged when the data were subjected to analysis by generalized scale invariance. It was between the intermittency of temperature, a number which can be determined for each segment of analysable flight from the temperature measurements, and the average over the flight segment of the photodissociation rate of ozone, which was calculable as a time series along the flight segment by taking the product of the 1Hz measurements of the local ozone concentration and the 1Hz measurements of the ozone photodissociation coefficient. In searching for a physical explanation of this correlation, it was realized that the common link between the quantities was that ozone photodissociation produces photofragments of atomic and molecular oxygen that recoil very fast, while temperature itself is the integral of the translational energy of all air molecules. The next step therefore was to ask if the intermittency of temperature was correlated with the average of the temperature itself over the flight segment: it was. One might think that because ozone is present at about 20km altitude in mixing ratios of about 2−3×10−6, the rapid quenching of the translational energies of the recoiling photofragments by molecular nitrogen and molecular oxygen would prevent any possible effects from showing up in the bulk, observed temperature. However, during the POLARIS mission, it was possible to fly the ER-2 near the terminator, the boundary between day and night, because at Arctic latitudes the planet was rotating slowly enough that it could fly legs in the same, stagnant air mass in both sunlight and darkness. These flights showed that the heating rate was significant, about 0.2Kper hour, and since heating in the stratosphere arises from the absorption of solar radiation by ozone, which leads to photodissociation, there is a prima facie case for considering non-local thermodynamic equilibrium effects from the recoiling fast photofragments. Two arguments may be deployed at this point, both from the theoretical literature; there are as yet no experiments on the translational speed distributions of atmospheric molecules.

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Conference papers on the topic "Serial correlation coefficient"

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Yu, Zhu, Zhang Ying, and Wen-Yi Chai. "Using correlation coefficient series to find the pattern of the correlation evolvement." In 2010 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2010. http://dx.doi.org/10.1109/icmlc.2010.5581042.

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Wang, Zhihua, Chengrui Liu, and Huimin Fu. "Correlation coefficient stationary series method for gyroscope random drift." In 2011 6th IEEE Conference on Industrial Electronics and Applications (ICIEA). IEEE, 2011. http://dx.doi.org/10.1109/iciea.2011.5975969.

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Cao, Xia-Xin, Chang-Qi Yan, Pu-Zhen Gao, and Zhong-Ning Sun. "Pressure Drop Correlations of Single-Phase and Two-Phase Flow in Rolling Tubes." In 14th International Conference on Nuclear Engineering. ASMEDC, 2006. http://dx.doi.org/10.1115/icone14-89237.

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A series of experimental studies of frictional pressure drop for single phase and two-phase bubble flow in smooth rolling tubes were carried out. The tube inside diameters were 15mm, 25mm and 34.5mm respectively, the rolling angles of tubes could be set as 10° and 20°, and the rolling periods could be set as 5s, 10s and 15s. Combining with the analysis of single-phase water motion, it was found that the traditional correlations for calculating single-phase frictional coefficient were not suitable for the rolling condition. Based on the experimental data, a new correlation for calculating singl

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de Souza, Luzia Vidal, Aurora T. R. Pozo, Joel M. C. da Rosa, and Anselmo Chaves Neto. "The boosting technique using correlation coefficient to improve time series forecasting accuracy." In 2007 IEEE Congress on Evolutionary Computation. IEEE, 2007. http://dx.doi.org/10.1109/cec.2007.4424619.

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Jiangeng Li, Qinglei Guo, and Yiheng He. "HMM training using correlation coefficients of time-series gene expression data." In 2012 24th Chinese Control and Decision Conference (CCDC). IEEE, 2012. http://dx.doi.org/10.1109/ccdc.2012.6244596.

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Petricic, Martin, and Alaa E. Mansour. "Estimation of the Long Term Correlation Coefficients by Simulation." In ASME 2010 29th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2010. http://dx.doi.org/10.1115/omae2010-20637.

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This paper proposes a simulation method for obtaining the estimate of the long term correlation coefficients between different low-frequency wave-induced loads acting on a ship hull. They are essential part of the load combination procedures in design and strength evaluations. Existing theory is limited to linear time-invariant systems with weakly stationary stochastic inputs such as waves during a single sea state (short-term). The simulation treats the non-stationary wave elevations during the ship’s entire life (long-term) as a sequence of different stationary Gaussian stochastic processes.

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Souza, Luzia Vidal de, Aurora T. R. Pozo, and Anselmo Chaves Neto. "An Empirical Study of Time Series Forecasting Using Boosting Technique with Correlation Coefficient." In Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007). IEEE, 2007. http://dx.doi.org/10.1109/isda.2007.152.

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Souza, Luzia Vidal de, Aurora T. R. Pozo, and Anselmo Chaves Neto. "An Empirical Study of Time Series Forecasting Using Boosting Technique with Correlation Coefficient." In Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007). IEEE, 2007. http://dx.doi.org/10.1109/isda.2007.4389707.

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Van Do, Luong, and Duong Tuan Anh. "Some improvements for time series subsequence join based on pearson correlation coefficients." In SoICT '16: Seventh International Symposium on Information and Communication Technology. ACM, 2016. http://dx.doi.org/10.1145/3011077.3011086.

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Batti, D., D. Peri, and E. F. Campana. "Geometry and Resistance of the IACC Systematic Series "Il Moro di Venezia"." In SNAME 17th Chesapeake Sailing Yacht Symposium. SNAME, 2005. http://dx.doi.org/10.5957/csys-2005-003.

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The geometry and bare hull resistance of the IACC systematic series “Il Moro di Venezia” are presented and analyzed. In the first part, the geometry of the model is described; then a number of comparisons is made, following the logic of development of the series. The parent model resistance is compared with that of models for which a single parameter has been varied. Variations concern the bow shape, the stern overhang, the prismatic coefficient, the midsection coefficient, the BWL/TC and LWL/BWL ratios, the displacement. The comparisons in some cases confirm already known trends, like the eff

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