Gotowe bibliografie tematyczne / AR(1) model

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  1. Artykuły w czasopismach
  2. Rozprawy doktorskie
  3. Książki
  4. Części książek
  5. Streszczenia konferencji
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Gotowa bibliografia na temat „AR(1) model”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 25 stycznia 2023

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Artykuły w czasopismach na temat "AR(1) model"

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Chan, K. S., Joseph D. Petruccelli, H. Tong, and Samuel W. Woolford. "A multiple-threshold AR(1) model." Journal of Applied Probability 22, no. 2 (June 1985): 267–79. http://dx.doi.org/10.2307/3213771.

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We consider the model Zt = φ (0, k)+ φ(1, k)Zt–1 + at (k) whenever rk−1<Zt−1≦rk, 1≦k≦l, with r0 = –∞ and rl =∞. Here {φ (i, k); i = 0, 1; 1≦k≦l} is a sequence of real constants, not necessarily equal, and, for 1≦k≦l, {at(k), t≧1} is a sequence of i.i.d. random variables with mean 0 and with {at(k), t≧1} independent of {at(j), t≧1} for j ≠ k. Necessary and sufficient conditions on the constants {φ (i, k)} are given for the stationarity of the process. Least squares estimators of the model parameters are derived and, under mild regularity conditions, are shown to be strongly consistent and as
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Tai‐Leung Chong, Terence. "The polynomial aggregated AR(1) model*." Econometrics Journal 9, no. 1 (March 1, 2006): 98–122. http://dx.doi.org/10.1111/j.1368-423x.2006.00178.x.

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Chan, K. S., Joseph D. Petruccelli, H. Tong, and Samuel W. Woolford. "A multiple-threshold AR(1) model." Journal of Applied Probability 22, no. 02 (June 1985): 267–79. http://dx.doi.org/10.1017/s0021900200037748.

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We consider the model Zt = φ (0, k)+ φ(1, k)Zt –1 + at (k) whenever r k−1<Z t−1≦r k , 1≦k≦l, with r 0 = –∞ and rl =∞. Here {φ (i, k); i = 0, 1; 1≦k≦l} is a sequence of real constants, not necessarily equal, and, for 1≦k≦l, {at (k), t≧1} is a sequence of i.i.d. random variables with mean 0 and with {at (k), t≧1} independent of {at (j), t≧1} for j ≠ k. Necessary and sufficient conditions on the constants {φ (i, k)} are given for the stationarity of the process. Least squares estimators of the model parameters are derived and, under mild regularity conditions, are shown to be strongly cons
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Vrbik, Jan. "Moments of AR(1)-Model Estimators." Communications in Statistics - Simulation and Computation 34, no. 3 (July 2005): 595–600. http://dx.doi.org/10.1081/sac-200068447.

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Sharafi, M., and A. R. Nematollahi. "AR(1) model with skew-normal innovations." Metrika 79, no. 8 (June 29, 2016): 1011–29. http://dx.doi.org/10.1007/s00184-016-0587-7.

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Li, M., Q. J. Wang, J. C. Bennett, and D. E. Robertson. "A strategy to overcome adverse effects of autoregressive updating of streamflow forecasts." Hydrology and Earth System Sciences 19, no. 1 (January 6, 2015): 1–15. http://dx.doi.org/10.5194/hess-19-1-2015.

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Abstract. For streamflow forecasting, rainfall–runoff models are often augmented with updating procedures that correct forecasts based on the latest available streamflow observations of streamflow. A popular approach for updating forecasts is autoregressive (AR) models, which exploit the "memory" in hydrological model simulation errors. AR models may be applied to raw errors directly or to normalised errors. In this study, we demonstrate that AR models applied in either way can sometimes cause over-correction of forecasts. In using an AR model applied to raw errors, the over-correction usually
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ZHENG, Wei, Da-wu GU, and Hai-ning LU. "Application of improved AR(1) model in DNS." Journal of Computer Applications 30, no. 3 (April 6, 2010): 736–39. http://dx.doi.org/10.3724/sp.j.1087.2010.00736.

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Bakouch, Hassan S., and Miroslav M. Ristić. "Zero truncated Poisson integer-valued AR(1) model." Metrika 72, no. 2 (March 24, 2009): 265–80. http://dx.doi.org/10.1007/s00184-009-0252-5.

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El-Sayed, Sayed Mesheal, Ahmed Amin El-Sheikh, Mohamed Khalifa Ahmed Issa, and Hadia Faried Mohamed Ahmed Azmy. "A CLOSED FORM OF BIASED AR(1) MODEL." Advances and Applications in Statistics 50, no. 3 (March 10, 2017): 191–99. http://dx.doi.org/10.17654/as050030191.

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Franses, Philip Hans. "A model selection test for an AR (1) versus an MA (1) model." Statistics & Probability Letters 15, no. 4 (November 1992): 281–84. http://dx.doi.org/10.1016/0167-7152(92)90163-y.

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Rozprawy doktorskie na temat "AR(1) model"

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Rastenė, Irma. "Testing and estimating changed segment in autoregressive model." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2011. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2011~D_20110628_134429-88914.

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In the doctoral dissertation, we consider problems of testing and estimating changed segment with unknown starting position and duration of epidemic state in the autoregressive first-order model. The proposed tests are based on partial sums of model residuals and model-parameter partial-estimator polygonal line processes. We derive asymptotic results for these processes in Holder spaces. The behavior of test statistics under the null hypothesis of no change and alternative is provided. Empirical power analysis has shown that tests are more powerful when absolute values of model parameter are q
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Morais, Telma Suely da Silva. "Abordagem Bayesiana do modelo AR(1) para dados em painel: uma aplicação em dados temporais de microarray." Universidade Federal de Viçosa, 2008. http://locus.ufv.br/handle/123456789/4016.

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Made available in DSpace on 2015-03-26T13:32:05Z (GMT). No. of bitstreams: 1 texto completo.pdf: 717763 bytes, checksum: e623d83648529a004b8aa2a3e4877433 (MD5) Previous issue date: 2008-12-05<br>We considered a Bayesian analysis of first order autoregressive, AR(1), panel data model, using exact likelihood function, comparative analysis of prior distributions and predictive distributions of future observations. The methodology efficiency was evaluated by a simulation study using three prior, which were related to different Generalized Beta distributions: symmetric, asymmetric and flat prior.
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Rastenė, Irma. "Autoregresinio modelio pasikeitusio segmento testavimas ir vertinimas." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2011. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2011~D_20110628_134442-76842.

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Disertacijoje nagrinėjamas pirmos eilės autoregresinio modelio pasikeitusio segmento testavimo ir vertinimo uždavinys. Aprašomo modelio epideminio pasikeitimo pradžia ir ilgis nėra žinomi. Pasiūlyti kriterijai pasikeitusio segmento testavimui, kurie pagrįsti modelio paklaidų įvertinių dalinių sumų ir modelio parametro dalinių įvertinių laužčių procesais. Šiems procesams gautos ribinės teoremos Hiolderio erdvėse. Nurodomas testų statistikų ribinis elgesys esant teisingai nulinei ir alternatyviajai hipotezėms. Iš empirinio kriterijų galios tyrimo rezultatų matyti, kad pasiūlytų testų galia didži
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Quiner, Trevor Elisha. "Chemopreventive Effects of Dietary Selenium and Soy Isoflavones in a Mouse Model of Prostate Cancer." BYU ScholarsArchive, 2010. https://scholarsarchive.byu.edu/etd/2541.

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Prostate cancer is the most commonly diagnosed non-skin cancer in men and the second leading cause of cancer death in the United States. Prostate cancer, like many cancers, is a disease that generally requires a long period of time to develop and grow before it becomes detectable. This long period of latency makes prostate cancer a candidate for dietary chemoprevention. Soy and selenium (Se), are associated with a decreased risk of prostate cancer. We previously showed that high dietary intake of selenium (Se) and soy isoflavones decreased the expression of the androgen receptor (AR) and AR-re
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Richmann, Michael K. "Comparison of mechanistic model with experimental observation : Part 1. The Ar(2p?) [to] Ar(1s?) emission signal in the pulse radiolysis of argon. Part 2. An absorption study of the argon 1s species /." The Ohio State University, 1991. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487759055158801.

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Yucer, Cem Tahsin. "Modelling The Evolution Of Demand Forecasts In A Production-distribution System." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12608109/index.pdf.

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In this thesis, we focus on a forecasting tool, Martingale Model of Forecast Evolution (MMFE), to model the evolution of forecasts in a production-distribution system. Additive form is performed to represent the evolution process. Variance-Covariance (VCV) matrix is defined to express the forecast updates. The selected demand pattern is stationary and it is normally distributed. It follows an Autoregressive Order-1 (AR(1)) model. Two forecasting procedures are selected to compare the MMFE with. These are MA (Moving average) and ES (Exponential smoothing) methods. A production-distribution mode
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Moser, Mathias, and Klara Zwickl. "Informal environmental regulation of industrial air pollution: Does neighborhood inequality matter?" WU Vienna University of Economics and Business, 2014. http://epub.wu.ac.at/4350/1/wp192.pdf.

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This paper analyzes if neighborhood income inequality has an effect on informal regulation of environmental quality, using census tract-level data on industrial air pollution exposure from EPA´s Risk Screening Environmental Indicators and income and demographic variables from the American Community Survey and EPA´s Smart Location Database. Estimating a spatial lag model and controlling for formal regulation at the states level, we find evidence that overall neighborhood inequality - as measured by the ratio between the fourth and the second income quintile or the neighborhood Gini coefficient
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Acosta, Argueta Lesly María. "Particle filtering estimation for linear and nonlinear state-space models." Doctoral thesis, Universitat Politècnica de Catalunya, 2013. http://hdl.handle.net/10803/134356.

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The sequential estimation of the states (filtering) and the corresponding simultaneous estimation of the states and fixed parameters of a dynamic state-space model, being linear or not, is an important probleminmany fields of research, such as in the area of finance. The main objective of this research is to estimate sequ entially and efficiently –from a Bayesian perspective via the particle filtering methodology– the states and/or the fixed parameters of a nonstandard dynamic state-spacemodel: one that is possibly nonlinear, non-stationary or non-Gaussian. The present thesis consists of sev
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Yi, Qilong. "Random effects and AR(1) models in longitudinal data analysis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/MQ49731.pdf.

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Tibulo, Cleiton. "MODELOS DE SÉRIES TEMPORAIS APLICADOS A DADOS DE UMIDADE RELATIVA DO AR." Universidade Federal de Santa Maria, 2014. http://repositorio.ufsm.br/handle/1/8334.

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Time series model have been used in many areas of knowledge and have become a current necessity for companies to survive in a globalized and competitive market, as well as climatic factors that have always been a concern because of the different ways they interfere in human life. In this context, this work aims to present a comparison among the performances by the following models of time series: ARIMA, ARMAX and Exponential Smoothing, adjusted to air relative humidity (UR) and also to verify the volatility present in the series through non-linear models ARCH/GARCH, adjusted to residues of the
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Książki na temat "AR(1) model"

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Kemp, Gordon C. R. Approximating the joint distribution of one-step ahead forecast errors in the AR(1) model. [Colchester]: University of Essex, Dept. of Economics, 1988.

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Nankervis, John C. The level and power of the bootstrap t-Test in the trend model with AR(1) errors. Guildford: Dept. of Economics, University of Surrey, 1994.

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Yi, Qilong. Random effects and AR(1) models in longitudinal data analysis. Ottawa: National Library of Canada, 2000.

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Lai, Pan-Yu. Some new results on two simple time series models: Prediction coverage for AR(1) and model building for jittery cosine waves. 1985.

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林東清, 林東清. 資訊管理：智慧化企業的核心競爭能力. 8-ме вид. 智勝出版, 2022. http://dx.doi.org/10.53106/9789575117856.

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&lt;p&gt;全新改版的資訊管理，綜觀最新資訊，解析未來科技發展趨勢，將「e化企業」的核心競爭能力改成「智慧化企業」的核心競爭能力，將帶領讀者建構高度完整的知識管理體系。本版包含三大主要特色：&lt;/p&gt; &lt;p&gt;1.強調智慧型科技與企業&lt;/p&gt; &lt;ul&gt; &lt;li&gt;第3章：講述AI的基本理念與各種學習理論，並就深度學習的特色與模式對人類工作及能力的影響，做了更新穎與深入的分析。&lt;/li&gt; &lt;li&gt;第5章：介紹蓬勃發展的許多AI型的產業，包括智慧型交通、智慧型醫療、智慧型金融、智慧型農漁牧業及智慧型商業等。&lt;/li&gt; &lt;li&gt;第12章：引介AI如何支援企業的經營模式，包括AI對企業的行銷、銷售、客服、生產、人力資源、行政管理等各個流程的支援。&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;2.追蹤各種新科技趨勢&lt;/p&gt; &lt;p&gt;介紹許多正在萌芽的新科技趨勢，包括元宇宙(Metaverse)、非同質化代幣(NFT)、AR/VR/MR（混合式實境）、線上線下虛實整合(Online Merge Offline, OMO)、Web 3.0、訂閱經濟、虛擬世界的電子商務，Gartner的10大科技趨勢，以及許多2022年後的新的科技行銷及數位轉型策略
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RUNCAN, PATRICIA. Consiliere și mentorare cu impact. Seria AUTENTIC. Vol. 2. EDITURA DE VEST, 2021. http://dx.doi.org/10.51820/autentic.2021.vol.2.

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"Prefață: Consiliere și mentorare cu impact Călăuzirea spirituală: de la „avva” Antichității la mentorul de azi Sfântul apostol Pavel le scria romanilor: „Dar cum vor chema pe Acela în care n-au crezut? Și cum vor crede în Acela despre care n-au auzit? Și cum vor auzi despre El, fără ca cineva să predice? Și cum vor predica, dacă n-au fost trimiși? Astfel, credința vine din cele auzite, iar cele auzite, prin Cuvântul Lui Dumnezeu.” (Romani 10: 14-15). Nimeni n-a plecat la propovăduire de capul lui. 1. Inițial, Isus „a chemat pe cine a vrut” (chemarea; vocația divină: gr. kaleo; lat. voco/are =
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Części książek na temat "AR(1) model"

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Miyashita, Toyokatsu. "An Application of AR Model to Multifrequency Hologram." In Acoustical Imaging, 351–60. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4613-0791-4_37.

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Reinsel, Gregory C. "Initial Model Building and Least Squares Estimation for Vector AR Models." In Springer Series in Statistics, 84–121. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4612-0679-8_4.

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Reinsel, Gregory C. "Initial Model Building and Least Squares Estimation for Vector AR Models." In Springer Series in Statistics, 74–110. New York, NY: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4684-0198-1_4.

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Lu, Zhenqiu, and Zhiyong Zhang. "Issues in Aggregating Time Series: Illustration Through an AR(1) Model." In Quantitative Psychology Research, 357–70. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19977-1_25.

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Tichavský, Petr, Ondřej Šembera, and Zbyněk Koldovský. "Blind Separation of Mixtures of Piecewise AR(1) Processes and Model Mismatch." In Latent Variable Analysis and Signal Separation, 304–11. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22482-4_35.

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Akkaya, Ayşen Dener, and Özlem Türker Bayrak. "A New Estimation Technique for AR(1) Model with Long-Tailed Symmetric Innovations." In Time Series Analysis and Forecasting, 39–63. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96944-2_4.

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Zenner, Markus. "Univariate AR(1) Models." In Lecture Notes in Economics and Mathematical Systems, 29–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-642-51876-8_2.

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Mijnheer, Joop. "The Asymptotic Distribution of a Sequential Estimator for the Parameter in an AR(1) Model With Stable Errors." In Asymptotic Methods in Probability and Statistics with Applications, 425–34. Boston, MA: Birkhäuser Boston, 2001. http://dx.doi.org/10.1007/978-1-4612-0209-7_30.

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Granić, Andrina. "Technology Acceptance and Adoption in Education." In Handbook of Open, Distance and Digital Education, 1–15. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0351-9_11-1.

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AbstractThe chapter provides a comprehensive and up-to-date insight into main research findings in the area of educational technology acceptance, adoption, and usage. Over the past decades, a variety of theoretical perspectives have been advanced to provide an understanding of the determinants of adoption of various technologies used to support the process of knowledge transfer and acquisition. Although some prominent theoretical approaches in educational contexts include Innovation Diffusion Theory (IDT), Unified Theory of Acceptance and Use of Technology (UTAUT), as well as Motivational Model (MM), research reveals the Technology Acceptance Model (TAM) as the most influential model and leading scientific paradigm in investigating acceptance of educational technology by students, teachers, and other stakeholders. Aiming to increase their predictive validity, in numerous empirical studies, models have been extended with different predictive factors, like the most often validated self-efficacy, subjective norm, perceived enjoyment, perceived playfulness, anxiety, social influence, system quality, and facilitating conditions. Research revealed electronic learning (e-learning) as the most common validated mode of delivery, followed by mobile learning (m-learning), learning management system (LMS), personal learning environment (PLE), and massive open online course (MOOC), along with different supportive facilitating technologies used in education such as social media platforms, teaching assistant robots, simulators, as well as virtual reality (VR) and augmented reality (AR) technologies. To enhance explanatory power, new developments in educational technology acceptance and adoption have suggested the need of integration of TAM and UTAUT with other contributing adoption and post-adoption theories and models, together with several established approaches from other fields.
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Shimizu, Kenichi. "Semiparametric AR(p)-ARCH(1) Models." In Bootstrapping Stationary ARMA-GARCH Models, 85–126. Wiesbaden: Vieweg+Teubner, 2010. http://dx.doi.org/10.1007/978-3-8348-9778-7_5.

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Streszczenia konferencji na temat "AR(1) model"

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Su, Guoguang, Hamn-Ching Chen, Je-Chin Han, and James D. Heidmann. "Computation of Flow and Heat Transfer in Two-Pass Rotating Rectangular Channels (AR=1:1, AR=1:2, AR=1:4) With 45-deg. Angled Ribs by Reynolds Stress Turbulence Model." In ASME Turbo Expo 2004: Power for Land, Sea, and Air. ASMEDC, 2004. http://dx.doi.org/10.1115/gt2004-53662.

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Numerical predictions of three-dimensional flow and heat transfer are presented for rotating two-pass rectangular channel with 45-deg rib turbulators. Three channels with different aspect ratios (AR=1:1; AR=1:2; AR=1:4) were investigated. Detailed predictions of mean velocity, mean temperature, and Nusselt number for two Reynolds numbers (Re = 10,000 and Re = 100,000) were carried out. The rib height is fixed as constant and the rib-pitch-to-height ratio (P/e) is 10, but the rib height-to-hydraulic diameter ratios (e/Dh) are 0.125, 0.094, and 0.078, for AR=1:1, AR=1:2, and AR=1:4 channel, resp
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Nagao, Tomonori, Mayumi Ohmiya, Theodore E. Simos, George Psihoyios та Ch Tsitouras. "Networked Ising-Sznajd AR-β Model". У NUMERICAL ANALYSIS AND APPLIED MATHEMATICS: International Conference on Numerical Analysis and Applied Mathematics 2009: Volume 1 and Volume 2. AIP, 2009. http://dx.doi.org/10.1063/1.3241433.

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Slama, Abdeldjalil. "On Testing Changes in Parameters of Contaminated AR(1) Model." In 2020 2nd International Conference on Mathematics and Information Technology (ICMIT). IEEE, 2020. http://dx.doi.org/10.1109/icmit47780.2020.9046977.

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Xu, Zhangyi, Fei Wang, Fei Chen, and Yun Bai. "Research on Quantitative Model of the Bullwhip Effect Based on AR(1) Demand." In 2011 International Conference on Management and Service Science (MASS 2011). IEEE, 2011. http://dx.doi.org/10.1109/icmss.2011.5998321.

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Ivanova, N. M., I. V. Belyev, Y. G. Leonov, Y. I. Matveev, and Y. V. Roslov. "Deep Model Barents-Kara Region Based on Complex Interpretation along Geotraverses 1-3 AR." In 2nd EAGE St Petersburg International Conference and Exhibition on Geosciences. European Association of Geoscientists & Engineers, 2006. http://dx.doi.org/10.3997/2214-4609-pdb.20.a004.

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Adam, Fia Fridayanti, Anang Kurnia, I. Gusti Putu Purnaba, and I. Wayan Mangku. "Prediction of Number of Claims using Poisson Linear Mixed Model with AR(1) random effect." In Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia. EAI, 2020. http://dx.doi.org/10.4108/eai.2-8-2019.2290464.

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Sun, Jing, Shengxian Wang, and Zhihui Fu. "The Effect of Autocorrelated Data on Taguchi Process Capability Index Cpm Based on AR(1) Model." In 2009 International Conference on Management and Service Science (MASS). IEEE, 2009. http://dx.doi.org/10.1109/icmss.2009.5301174.

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Su, Yan, Ya-Ping Huang, and Xia-Ying Su. "goodness-of-fit test for normally distributed ar(1) disturbances of the multiple linear regression model." In 2014 International Conference on Computer Science and Electronic Technology. Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/iccset-14.2015.72.

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Hoi, Yiemeng, Mark Van Doormaal, Yu-Qing Zhou, Xiaoli Zhang, R. Mark Henkelman, and David A. Steinman. "Degree of Retrograde Flow and Its Effect on Local Hemodynamics and Plaque Distribution in an Aortic Regurgitation Murine Model of Atherosclerosis." In ASME 2011 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2011. http://dx.doi.org/10.1115/sbc2011-53161.

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Previously, Zhou et al. [1] presented a novel mouse model of aortic valve regurgitation (AR) to explore the effect of altered hemodynamics on atherogenesis. In these ldlr−/− mice with AR, extensive atherosclerotic plaque was found along the naturally lesion-free descending thoracic (DTAo) and abdominal aorta (AbAo), with distinct spatial distributions suggestive of a strong local hemodynamic influence (Fig. 1, top). Doppler ultrasound measurement showed that both DTAo and AbAo of the AR mice experienced an oscillatory flow pattern induced by the diastolic retrograde flow, as opposed to the con
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Wardell, Suzanne E., Alexander P. Yllanes, John D. Norris, James P. Stice, Hannah White, Ronald A. Fleming, Jay C. Strum, William R. Moore, and Donald P. McDonnell. "Abstract 1588: Effects of the selective CYP17-lyase and androgen receptor (AR) inhibitor, seviteronel, and the cyclin-dependent kinase (CDK) 4/6 inhibitor, G1T38, on tumor growth in an AR-V7+ castration-resistant prostate cancer (CRPC) xenograft model." In Proceedings: AACR Annual Meeting 2017; April 1-5, 2017; Washington, DC. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7445.am2017-1588.

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Raporty organizacyjne na temat "AR(1) model"

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Ervin, Kelly, Karl Smink, Bryan Vu, and Jonathan Boone. Ship Simulator of the Future in virtual reality. Engineer Research and Development Center (U.S.), September 2022. http://dx.doi.org/10.21079/11681/45502.

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The Army’s modernization priorities include the development of augmented reality and virtual reality (AR/VR) simulations for enabling the regiment and increasing soldier readiness. The use of AR/VR technology at the U.S. Army Engineer Research and Development Center (ERDC) is also growing in the realm of military and civil works program missions. The ERDC Coastal and Hydraulics Laboratory (CHL) has developed a ship simulator to evaluate bay channels across the world; however, the current simulator has little to no physical realism in nearshore coastal regions (Figure 1). Thus, the ERDC team is
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