This article was originally published on Built In by Eric Kleppen. Variance is a powerful statistic used in data analysis and machine learning. It is one of the four main measures of variability along ...

We consider a wavelet thresholding approach to adaptive variance function estimation in heteroscedastic nonparametric regression. A data-driven estimator is constructed by applying wavelet ...

One of the key assumptions of regression is that the variance of the errors is constant across observations. Correcting for heteroscedasticity improves the efficiency of the estimates. If you had a ...

For binomial and Poisson distributions, the scale parameter has a value of 1. The variance of Y is for the binomial distribution and for the Poisson distribution. Overdispersion occurs when the ...

We develop locally D-optimal designs for nonlinear models when the variance of the response is a function of its mean. Using the two-parameter Michaelis-Menten model as an example, we show that the ...