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02187aam a2200385 i 4500 001 50B9EFB0440211EF98CC15ED37ECA4DB 003 SILO 005 20240717010108 008 230513t20232023enka b 001 0 eng 010 $a 2023017747 020 $a 1108837778 020 $a 9781108837774 035 $a (OCoLC)1346530967 040 $a LBSOR $b eng $e rda $c DLC $d UKMGB $d OCLCF $d YDX $d OCLCQ $d GRU $d KEI $d GZM $d OCLCO $d YDX $d IUL $d SILO 042 $a pcc 050 00 $a QA280 S23 2023 084 $a QH 237 $2 rvk 084 $a 417.6 $2 njb/10 100 1 $a SaÌnchez, Juana, $e author. 245 10 $a Time series for data scientists : $b data management, description, modeling and forecasting / $c Juana Sanchez. 264 1 $a Cambridge, United Kingdom ; $b Cambridge University Press, $c 2023. 300 $a xii, 463 pages : $b illustrations (some color) ; $c 26 cm 504 $a Includes bibliographical references and index. 505 0 $a Introduction to time series data -- Smoothing and decomposing a time series -- Summary statistics of stationary time series -- The algebra of differencing and backshifting -- Stationary stochastic processes -- ARIMA(p,d,q)(P,D,Q)f modeling and forecasting -- Latent process models for time series -- Vector autoregression -- Classical regression with ARMA residuals -- Machine learning methods for time series. 520 $a "Learn by doing with this guide to classical and contemporary machine learning approaches to time series data analysis. With datasets, commented R programs, case studies and quizzes, this is an essential and accessible resource for undergraduate and graduate students in statistics and data science, and researchers in data-rich disciplines"-- $c Provided by publisher. 650 0 $a Time-series analysis $v Textbooks. 650 0 $a Data mining $x Statistical methods $v Textbooks. 650 0 $a Multivariate analysis $v Textbooks. 650 0 $a Time-series analysis $x Data processing. 650 0 $a R (Computer program language) 776 08 $i ebook version : $z 9781108942812 941 $a 1 952 $l USUX851 $d 20240717024058.0 956 $a http://locator.silo.lib.ia.us/search.cgi?index_0=id&term_0=50B9EFB0440211EF98CC15ED37ECA4DB 994 $a C0 $b IWAInitiate Another SILO Locator Search