# Statistics

## 1508 Submissions

[3] **viXra:1508.0265 [pdf]**
*submitted on 2015-08-27 02:35:07*

### A Study of Improved Chain Ratio-cum-Regression type Estimator for Population Mean in the Presence of Non- Response for Fixed Cost and Specified Precision

**Authors:** B. B. Khare, Habib Ur Rehman, U. Srivastava

**Comments:** 10 Pages.

In this paper, a study of improved chain ratio-cum regression type estimator for population
mean in the presence of non-response for fixed cost and specified precision has been made.
Theoretical results are supported by carrying out one numerical illustration.

**Category:** Statistics

[2] **viXra:1508.0256 [pdf]**
*submitted on 2015-08-27 02:50:36*

### Estimation of Ratio and Product of Two Population Means Using Auxiliary Characters in the Presence of Non Response

**Authors:** B. B. Khare

**Comments:** 8 Pages.

The auxiliary information is used in increasing the efficiency of the estimators for the
parameters of the populations such as mean, ratio, and product of two population means. In this context, the estimation procedure for the ratio and product of two population means using auxiliary characters in special reference to the non response problem has been discussed.

**Category:** Statistics

[1] **viXra:1508.0142 [pdf]**
*replaced on 2016-02-24 08:21:59*

### Issues in the Multiple Try Metropolis Mixing

**Authors:** L. Martino, F. Louzada

**Comments:** 15 Pages. To appear in Computational Statistics

The multiple Try Metropolis (MTM) algorithm is an advanced MCMC technique based on drawing and testing several candidates at each iteration of the algorithm. One of them is selected according to certain weights and then it is tested according to a suitable acceptance probability. Clearly, since the computational cost increases as the employed number of tries grows, one expects that the performance of an MTM scheme improves as the number of tries increases, as well. However, there are scenarios where the increase of number of tries does not produce a corresponding enhancement of the performance. In this work, we describe these scenarios and then we introduce possible solutions for solving these issues.

**Category:** Statistics