Estimation of Location and Scale Parameters in a Truncated Grouped Sech Square Distribution
截断分组双曲正割平方分布的位置与尺度参数估计AI 解读 ↓
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截断分组双曲正割平方分布的位置与尺度参数估计AI 解读 ↓
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The iterative calculations required to obtain the maximum likelihood estimates of α and β in the distribution function dF(z) = e z /(1 + e z )2 dz, where z = α +βx, are presented for doubly truncated, upper and lower truncated, and untruncated grouped samples. The calculations needed to obtain the maximum likelihood estimator of Pareto's constant are also given for a lower truncated grouped sample with both equal and unequal grouping. Asymptotic variances and covariances are derived for all estimators considered.
极端分位数回归加权最大似然估计量的存在性与一致性
Estimating extreme conditional quantiles faces two major challenges: understanding complex nonlinear relationships between variables and accurately extrapolating into the tails of the distribution, where data are sparse. To address both issues, we introduce a novel approach that combines the theoretical framework of block maxima with the predictive power of generalized random forests. The conditional distribution of maxima is modeled by a generalized extreme value (GEV)…
基于分位数的 Kumaraswamy–Teissier 自回归移动平均模型
This paper introduces a quantile-based Kumaraswamy-Teissier autoregressive moving average (KTARMA) model for positive-valued time series. Leveraging the flexibility of the extended Kumaraswamy-Teissier distribution within an observation-driven framework, the random component of the distribution is conditioned on the historical process and time-varying covariates, and is parameterized explicitly via its $ρ$-th conditional quantile, where $ρ\in (0,1)$. To capture temporal…
弱依赖非线性时间序列模型准似然估计量的一致高斯近似
We study estimation and inference for a semiparametric class of time series models that specify only the conditional expectation, which is a known link function applied to a linear combination of past observations and covariates. The class covers count, binary, bounded and conditionally heteroskedastic responses within a single formulation, and the parameter is estimated by a quasi-likelihood estimating equation based on the first conditional moment. Under stationarity and a…
条件期望分位数的估计风险
We establish the consistency and asymptotic normality of a two-step estimator of conditional expectiles in the context of conditional scale models. We first estimate the conditional variance parameters by quasi-maximum likelihood and then compute the unconditional expectile of the innovations using the empirical distribution of the standardized residuals. We show how replacing true innovations with standardized residuals affects the asymptotic variances of both conditional…
利用多分位数稳健检验多变量波动率的结构变化
We propose an omnibus nonparametric test for structural changes in the multivariate volatility matrix. The test aggregates bounded generalized quantile scores over a range of quantile levels and has a weighted leave-$q$-out $U$-statistic representation. Deleting nearby index pairs renders the centering effect induced by serial dependence asymptotically negligible. All quantities required for implementation, including the variance estimator used for standardization, are…
网络模型中基于成对差分的分布回归方法
I develop an estimation and inference framework for distribution regression in dyadic network settings with two-way fixed effects that vary across thresholds of the outcome. I show that identification of the structural parameters is achieved through binarization of the outcome at each threshold, and estimate the model by conditional maximum likelihood, which "differences out" the fixed effects and circumvents the incidental parameter problem. The estimator remains…