Minimum variance unbiased estimates of the inverse Gaussian distribution function for all possible cases are given. A direct relationship is established between its density function and the normal ...

This column is the fourth in a series on parameter estimation, leading up to the justly famous Kalman filter. The discipline is based on the fact that our knowledge of the state of any real-world ...

You can use the CDFPLOT statement to fit any of six theoretical distributions (beta, exponential, gamma, lognormal, normal, and Weibull) and superimpose them on the cdf plot. The following statements ...

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 ...

A robust procedure is developed for estimating density functions from data. It requires the existence of a parametric function, called the key function, to give a first approximation to the density ...

The market demand curve and the normal curve are different in several different ways. The shape of the demand curve, its purpose and the function that defines it are all different from that of the ...

SAS/INSIGHT software provides tests for the null hypothesis that the input data values are a random sample from a normal distribution. These test statistics include the Shapiro-Wilk statistic (W) and ...