Results 151 to 160 of about 2,000,076 (197)

Generalized Empirical Distribution Function

SSRN Electronic Journal, 2012
One way to produce Value at Risk (VAR) for financial institution is to apply previously observed movements of the market underlying parameters (interest rates, for example) to their current values in order to obtain starting point of the analysis. This way multiple starting points can be created.
openaire   +1 more source

Empirical distribution function under heteroscedasticity

Statistics, 2011
Neglecting heteroscedasticity of error terms may imply the wrong identification of a regression model (see appendix). Employment of (heteroscedasticity resistent) White's estimator of covariance matrix of estimates of regression coefficients may lead to the correct decision about the significance of individual explanatory variables under ...
openaire   +1 more source

Folded Empirical Distribution Function Curves—Mountain Plots

The American Statistician, 1995
Abstract Various graphical methods are available for displaying one or more univariate distributions. In this article the folded empirical distribution function curve, or mountain plot, is described and compared to alternative plots. The mountain plot is a graphical display that complements other visual representations of the data, as is illustrated ...
openaire   +1 more source

Empirical functions for atmospheric aerosol size distributions

Journal of Aerosol Science, 1989
Abstract Two- and three-parameter functions are proposed for fitting aerosol size distributions that have a maximum and exhibit log-linear behaviour at large radii. To demonstrate their usefulness, we fit the functions to measured size distributions of insoluble particles recovered from sections of Greenland and Antarctic ice cores.
Michael Ram   +2 more
openaire   +1 more source

Empirical Distribution Functions

2017
In this chapter we are interested in functional limit theorems for the empirical distribution function associated to a stationary and strongly mixing sequence of random variables with values in \(\mathrm{I\!R}^d\).
openaire   +1 more source

Home - About - Disclaimer - Privacy