Showing 1 - 10 of 20
dependent errors, are considered for observations over time, space or space-time. Consistency and asymptotic normality of … many in which consistency of a vector of parameter estimates (which converge at different rates) cannot be established by … present a generic consistency result.J …
Persistent link: https://www.econbiz.de/10011126136
We provide a direct proof for consistency and asymptotic normality of Gaussian maximum likelihood estimators for causal …
Persistent link: https://www.econbiz.de/10011126193
We provide a direct proof for consistency and asymptotic normality of Gaussian maximum likelihood estimators for causal …
Persistent link: https://www.econbiz.de/10011126410
This paper examines the Gaussian maximum likelihood estimator (GMLE) in the context of a general form of spatial autoregressive and moving average (ARMA) processes with finite second moment. The ARMA processes are supposed to be causal and invertible under the half-plane unilateral order, but...
Persistent link: https://www.econbiz.de/10011126532
This paper studies the sparsistency and rates of convergence for estimating sparse covariance and precision matrices based on penalized likelihood with nonconvex penalty functions. Here, sparsistency refers to the property that all parameters that are zero are actually estimated as zero with...
Persistent link: https://www.econbiz.de/10011071205
depending on a single smoothing number. Incorporating also a regression parameter (β) which, when non-zero, indicates … cointegration, the consistency proof of these implicitly-defined estimates is nonstandard due to the β estimate converging faster …
Persistent link: https://www.econbiz.de/10011071412
fixed-design regression, giving a single central limit theorem which indicates how error spectral behavior at only zero … regression estimates can be Studentized in the absence of previous knowledge of which form of dependence pertains, and show also …
Persistent link: https://www.econbiz.de/10010745997
to a nonparametric regression function. The procedure employs a recent projection interpretation of popular kernel … conditions are satisfied in a regression and a time series autoregression under weak conditions. …
Persistent link: https://www.econbiz.de/10010746685
We develop inference tools in a semiparametric regression model with missing response data. A semiparametric regression … responses are imputed using the semiparametric regression method the empirical log-likelihood is asymptotically a scaled chi …
Persistent link: https://www.econbiz.de/10010928736
We provide a proof of the consistency and asymptotic normality of the estimator suggested by Heckman (1990) for the …
Persistent link: https://www.econbiz.de/10010745509