Hands On Time Series Analysis with R: Perform Time Series Analysis and Forecasting Using R (Record no. 119041)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01953nam a2200193 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240529110655.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 191128b ||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781788629157 |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 005.133 |
| Item number | KRI |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Krispin, Rami |
| 9 (RLIN) | 45454 |
| 245 ## - TITLE STATEMENT | |
| Title | Hands On Time Series Analysis with R: Perform Time Series Analysis and Forecasting Using R |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc. | Birmingham |
| Name of publisher, distributor, etc. | Packt Publishing Ltd. |
| Date of publication, distribution, etc. | 2019 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 433p |
| 500 ## - GENERAL NOTE | |
| General note | 1. Introduction to Time Series Analysis and R; Technical requirements; Time series data; Historical background of time series analysis; Time series analysis<br/>2. Working with Date and Time Objects; Technical requirements; The date and time formats; Date and time objects in R<br/>3. The Time Series Object; Technical requirement; The Natural Gas Consumption dataset; The attributes of the ts class<br/>4. Working with zoo and xts ObjectsTechnical requirement; The zoo class<br/>5. Decomposition of Time Series Data; Technical requirement; The moving average function<br/>6. Seasonality analysis technical requirement seasonality types Seasonal analysis with descriptive statistics<br/>7. Correlation analysis technical requirement correlation between two variables Lags analysis<br/>The autocorrelation function the partial autocorrelation function Lag plots <br/>Causality analysis<br/>8. Forecasting strategies technical requirement the forecasting workflow training approaches <br/>9. Forecasting with linear regression technical requirement the linear regression<br/>10. Forecasting with Exponential smoothing models technical requirement ; forecasting with moving average models<br/>11. Forecasting with ARIMA models Technical requirement ;The stationary process<br/>12. Forecasting with machine learning models technical requirement why and when should we use machine learning <br/><br/> |
| 600 ## - SUBJECT ADDED ENTRY--PERSONAL NAME | |
| Personal name | R (Computer Program Language) - Time - Series Analysis |
| 9 (RLIN) | 45455 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Book |
| Call number prefix | 005.133 |
| Call number suffix | KRI |
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