Measures of variation are statistical measures which assist in describing the distribution data set. These either used separately or together to give a wide variety ways measuring variability data. Researchers and mathematicians found out that these were not perfect, they violated algebraic laws possessed some weakness could ignore. As result facts, new measure known as geometric was formulated...

We consider point estimation and inference based on modifications of the profile likelihood in models for dyadic interactions between n agents featuring agent-specific parameters. This setup covers the β-model of network formation and generalizations thereof. The maximum-likelihood estimator of such models has bias and standard deviation of O(n−1) and so is asymptotically biased. Estimation bas...

It has recently become possible to screen thousands of markers to detect genetic causes of common diseases. Along with this potential comes analytical challenges, and it is important to develop new statistical tools to identify markers with causal effects and accurately estimate their effect sizes. Knowledge of the proportion of markers without true effects (p0) and the effect sizes of markers ...

This paper considers an Type I Generalized Half Logistic Distribution. We discussed the scale (σ) and shape (θ) parameters estimation using the median ranks method (Benard‟s approximation). Rama Krishna(2008) 1 studied the Type I Generalized Half Logistic Distribution scale (σ) and shape (θ) parameters estimation using the Least Square Method in two step estimation method. Also we computed Aver...

Abstract: Suppose Y is a response variable, possibly multivariate, with a density function f(y|x, v;β) conditional on the covariates (x, v) where x and v are vectors and β is a vector of unknown parameters. The authors consider the problem of estimating β when data on the covariate vector v are available for all observations while data on the covariate x are missing at random. They compare seve...