Can the t distribution be used in the statistical analysis of language usage?

(2) Student's t-distribution is less peaked than a normal distribution, at the same time, t-distribution has “fatter tails”. In this way, it seems like that ... The t distribution provides a good way to perform one sample tests on the mean when the population variance is not known provided the population is normal. A standard multivariate Student's t random vector can be written as a multivariate normal vector whose covariance matrix is scaled by the reciprocal of a Gamma ... Mar 18, 2022 ... Implementation in R: Here is some code to implement this MLE analysis in R in a simple way, without analytic computation of the gradient or ... Sep 3, 2018 ... The skew normal family is great for modeling skewed gaussian data, and the student t distribution is great for outliers. Nov 15, 2022 ... The entropy of a Student t random variable with ν degrees of freedom is asymptotically \frac{1}{2} + \frac{\log 2\pi}{2} + \frac{1}{\nu} for large Jun 29, 2023 ... Hello, I have a hierarchical regression models that seems to follow a student T distribution but I can't seem to get a high enough “spike” ... tcdf( computes the Student t distribution probability between lowerbound and upperbound for the specified df (degrees of freedom), which must be > 0. The Student- t distribution is commonly used in finance and risk management, particularly to model conditional asset returns for which the tails of the normal ... Nov 19, 2021 ... ... student t-distribution instead of a random noise Gaussian distribution. The proposed framework was named TED-GAN, with T from the t-distribution ...