Progress in Applied Statistics Research

Computers have taken a permanent place in almost every human endeavour in the last 20 years. This infiltration requires a learning process on the part of the people utilising them and realising where and how they can be best used beyond the basic and obvious applications. Statistics is an example of their application in many diverse fields to reach conclusions and make projections never before possible. Beyond this, applied statistics is rapidly becoming not only an instrument, but an integral part of the advance of knowledge. There are many fields such as medicine, biology, weather prediction, military planning, and many others where the statistical studies are essential before the next step can be taken. This new book presents the latest research in the field.

Table of Contents:
Preface; An Approximate Fast Bayesian Algorithm for the Analysis and Forecasting of the Lognormal Time Series; Efficient Uniform Designs for Mixture Experiments in Three and Four Components; Design of Accelerated Life Tests for Periodic Inspection with Burr Type III Distributions: Models, Assumptions and Applications; Parameter Estimation Using Cressie-Read Divergence Measures with Exponential Grouped Censored Data; Estimating the Variance Components of Accelerated Degradation Models; On The Ratio of The Symmetric Differences of Order Statistics; Measuring the Surface Roughness Using the Spatial Statistics Application; Diallel Crosses with Block Sizes Three; On Characterizing Distributions by Conditional Expectations of Function of Generalized Order Statistics; Estimating the Location and Scale Parameters Using Ranked Set Sampling; pp. 245-252; Robust Estimation in Calibration Models Using the Student-t Distribution; Useful Results for the Renewal and the Alternating Renewal Process; Classification of Multivariate Repeated Measures Data with Temporal Autocorrelation; Bayesian Estimation for the AR(1) Model Using Asymmetric Loss Functions;; Bayesian Modelling for Recurrent Lifetime Data with a Non Homogeneous Poisson Process with a Frailty Term with a Gamma or Inverse Gaussian distribution.; Local Influence for Measurement Error Regression Models for the Analysis of Pretest/Posttest Data; A Transition Model for an Ordered Cluster of Mixed Continuous and Discrete Responses with Non-Monotone Missingness; On A Nonbinary S-Optimal Design Over a Class of Minimally Connected Binary Row-Column Designs; The Erlangian Machine Interference Model: Er/M/2/k/N With Balking, Reneging and Heterogeneous Repairmen; Some Extensions to Double Ranked Set Sampling; Index.