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利用非参数回归检查模型AI 解读

The use of nonparametric regression is explored to check the fit of a parametric regression model. The principal aim is to check the validity of the regression curve rather than necessarily to detect outliers. A pseudo likelihood ratio test is developed to provide a global assessment of fit and simulation bands are used to indicate the nature of departures from the model. The types of data considered include discrete response variables, where standard diagnostic techniques…

非参数回归在模型检验中的应用AI 解读

The use of nonparametric regression is explored to check the fit of a parametric regression model. The principal aim is to check the validity of the regression curve rather than necessarily to detect outliers. A pseudo likelihood ratio test is developed to provide a global assessment of fit and simulation bands are used to indicate the nature of departures from the model. The types of data considered include discrete response variables, where standard diagnostic techniques…

《自回归时间序列集合的估计与假设检验》的公式更正AI 解读

Formulae for ψ^(α) and σ^2(α) on p. 87 do not hold for all α, since they may not satisfy the constraint σ^2(α)≤ψ^(α) induced by the parameterization. Then the expressions do not give maximum likelihood estimates for given α. When the inequality fails, the maximum likelihood estimates are on the boundary of the parameter space, namely where σ2=ψ⁠. The maximum then occurs for σ^2(α)=ψ^(α) both equal to σ^2(α) given at p. 88, shortly after (7). Formula (6) still applies,…

多条自回归时间序列的估计与假设检验AI 解读

The analysis of a number of independent first-order autoregressive time series is considered in a normal theory context. A model is studied which allows for nonstation-ary and nonidentical distribution of the series caused by both fixed effect and random effect components.

多组自回归时间序列的估计与假设检验AI 解读

The analysis of a number of independent first-order autoregressive time series is considered in a normal theory context. A model is studied which allows for nonstation-ary and nonidentical distribution of the series caused by both fixed effect and random effect components.