brockwell时间序列理论与方法第一版+第二版(中文版)
2019-12-21 21:44:48 32.21MB 时间序列
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Hamilton-Time Series Analysis Hamilton-Time Series Analysis Hamilton-Time Series Analysis
2019-12-21 21:39:20 24.74MB Hamilton -Time Series Analysis
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论文提出了一种新的融合空间尺度特征的时空序列预测建模方法。
2019-12-21 21:32:06 5.11MB time series
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Selected solutions to introduction to time series from Prof. Brockwell
2019-12-21 21:25:00 264KB Brockwell Time Series Solutions
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Practical Time Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python 英文无水印原版pdf pdf所有页面使用FoxitReader、PDF-XChangeViewer、SumatraPDF和Firefox测试都可以打开 本资源转载自网络,如有侵权,请联系上传者或csdn删除 查看此书详细信息请在美国亚马逊官网搜索此书
2019-12-21 21:22:34 11.73MB Practical Time Series Analysis
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7_Series_XPE_2016_1 FPGA功耗评估
2019-12-21 21:18:15 3.46MB FPGA功耗评估
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FANUC Series 0i-MODEL MF维修说明书 B-64605CM-01
2019-12-21 21:15:59 11.37MB FANUC 0i MF 维修说明书
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Time Series Analysis With Applications in R (Springer)
2019-12-21 21:09:25 5.44MB R Time Series Analysis
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Aimed at econometricians who have completed at least one course in time series modeling, Multiple Time Series Modeling Using the SAS VARMAX Procedure will teach you the time series analytical possibilities that SAS offers today. Estimations of model parameters are now performed in a split second. For this reason, working through the identifications phase to find the correct model is unnecessary. Instead, several competing models can be estimated, and their fit can be compared instantaneously. Consequently, for time series analysis, most of the Box and Jenkins analysis process for univariate series is now obsolete. The former days of looking at cross-correlations and pre-whitening are over, because distributed lag models are easily fitted by an automatic lag identification method. The same goes for bivariate and even multivariate models, for which PROC VARMAX models are automatically fitted. For these models, other interesting variations arise: Subjects like Granger causality testing, feedback, equilibrium, cointegration, and error correction are easily addressed by PROC VARMAX. One problem with multivariate modeling is that it includes many parameters, making parameterizations unstable. This instability can be compensated for by application of Bayesian methods, which are also incorporated in PROC VARMAX. Volatility modeling has now become a standard part of time series modeling, because of the popularity of GARCH models. Both univariate and multivariate GARCH models are supported by PROC VARMAX. This feature is especially interesting for financial analytics in which risk is a focus. This book teaches with examples. Readers who are analyzing a time series for the first time will find PROC VARMAX easy to use; readers who know more advanced theoretical time series models will discover that PROC VARMAX is a useful tool for advanced model building.
2019-12-21 21:07:23 22.73MB sas
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俄罗斯系列丛书一直深受数学专业学生的喜爱,本资源是那汤松 第五版 实变函数论(对课后答案和勘误做了总结),是实变(十遍)的经典教材!
2019-12-21 20:57:01 40.17MB Analytics Russian series Real
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