Titlebook: Advances in Time Series Methods and Applications; The A. Ian McLeod Fe Wai Keung Li,David A. Stanford,Hao Yu Book 2016 Springer Science+Bus

Little

The Doubly Adaptive LASSO for Vector Autoregressive Models, in regression analysis for their advantage of simultaneous variable selection and parameter estimation, and also have been applied to autoregressive time series models. We propose the doubly adaptive LASSO (daLASSO), or PLAC-weighted adaptive LASSO, for modelling stationary vector autoregressive pr

Malfunction

容易生皺紋

涂掉

The Portmanteau Tests and the LM Test for ARMA Models with Uncorrelated Errors,odels with uncorrelated errors. Under the assumption that the error is not independent, the classical portmanteau tests and LM test are asymptotically distributed as a weighted sum of chi-squared random variables that can be far from the chi-squared distribution. To conduct the tests, we must estima

拋射物

Generalized , Tests for Estimating Functions with Serial Dependence,dures allow for general forms of serial dependence and heteroskedasticity, and can be implemented using any root-. consistent restricted estimator. The asymptotic distribution of the proposed statistic is established under weak regularity conditions. We show that earlier .-type statistics are includ

功多汁水

Regression Models for Ordinal Categorical Time Series Data,al response at a given time are ordinal, the regression analysis for such ordinal categorical time series becomes more complex. In this paper, we first develop a lag 1 transitional logit probabilities based correlation model for the multinomial responses recorded over time. This model is referred to

戲法

Adenoma

,Improved Seasonal Mann–Kendall Tests for Trend Analysis in Water Resources Time?Series,ies modelling of water resources and environmental systems. Elsevier, New York, 2005 [.]). One popular procedure is the seasonal Mann–Kendall tau test for detecting monotonic trend in seasonal time series data with serial dependence (Hirsch and Slack in Water Resour Res 20(6):727–732, 1984 [.]). How