JSTOR Daily

Estimation of the mean of a univariate normal distribution when the variance is not known

We consider the problem of estimating the first k coefficients in a regression equation with k + 1 variables. For this problem with known variance of innovations, the neutral Laplace weighted-average ...
Scientific Research Publishing

Fernandez-de-Cossio-Diaz, J. (2017) Truncated Normal: Compute Mean and Variance of the Univariate Truncated Normal Distribution (Works Far from the Peak).

ABSTRACT: A black hole is treated as a self-contained, steady state, spherically symmetric, 4-dimensional spatial ball filled with blackbody radiation, which is embedded in 3-D space. To model the ...
GitHub

basic-normal-distribution.rmd

Observed data are $latex y_i$ where $latex i=1, \ldots, I$. The data is modelled as independent observations drawn from a normal distribution with unknown variance ...
JSTOR Daily

Mixed Model Variance Analysis with Normal Error and Possibly Non-Normal Other Random Effects: Part I: The Univariate Case

The mixed model with one factor represented by fixed effects, one factor by random effects, and a normal error, has often stipulated that these random effects be a sample drawn from a normally ...
IEEE

Shun Matsuura

Bayesian Information Criterion,Data Distribution,Distribution Of Points,Exact Distribution,Gaussian Mixture Distribution,K-means Algorithm,Markov Chain Monte Carlo,Mixture Distribution,Non-informative ...
Nature

Shrinkage Estimation and Balanced Loss Functions in Multivariate Normal Distribution

Recent advances in estimation techniques have underscored the growing importance of shrinkage estimation and balanced loss functions in the analysis of multivariate normal distributions. These ...