A STUDY ON BOOTSTRAP CONFIDENCE INTERVALS OF SOFTWARE RELIABILITY MEASURES BASED ON AN INCOMPLETE GAMMA FUNCTION MODEL

This paper focuses on the generalization of several software reliability models and the derivation of confidence intervals of reliability assessment measures. First we propose a gamma function model as a generalized model, and discuss how to obtain the confidence intervals from a data set by using a bootstrap scheme when the size of the data set is small. A two-parameter numerical differentiation method is applied to the data set to estimate the model parameters. We also show several numerical illustrations of software reliability assessment.

Get full-text (via PubEx)

Interval estimations of software reliability and optimal release time based on better bootstrap confidence intervals

2013 IEEE International Conference on Industrial Engineering and Engineering Management ◽

10.1109/ieem.2013.6962455 ◽

2013 ◽

Cited By ~ 1

Author(s):

Shinji Inoue ◽

Shigeru Yamada

Keyword(s):

Confidence Intervals ◽

Software Reliability ◽

Release Time ◽

Bootstrap Confidence Intervals

Get full-text (via PubEx)

ON THE INCOMPLETE GAMMA FUNCTION AND ITS NEUTRIX CONVOLUTION FOR NEGATIVE INTEGERS

Eurasian Mathematical Journal ◽

10.32523/2077-9879-2019-10-1-30-51 ◽

2019 ◽

Vol 10 (1) ◽

pp. 30-51

Author(s):

Mongkolsery Lin ◽

◽

Brian Fisher ◽

Somsak Orankitjaroen ◽

◽

...

Keyword(s):

Gamma Function ◽

Incomplete Gamma Function

Get full-text (via PubEx)

Two-Condition Within-Participant Statistical Mediation Analysis: A Path-Analytic Framework

10.31234/osf.io/4su2j ◽

2019 ◽

Author(s):

Amanda Kay Montoya ◽

Andrew F. Hayes

Keyword(s):

Confidence Intervals ◽

Indirect Effect ◽

Mediation Analysis ◽

Analytic Approach ◽

Analytic Framework ◽

Hypothesis Tests ◽

Bootstrap Confidence Intervals ◽

Complex Models ◽

Path Analytic ◽

Statistical Mediation Analysis

Researchers interested in testing mediation often use designs where participants are measured on a dependent variable Y and a mediator M in both of two different circumstances. The dominant approach to assessing mediation in such a design, proposed by Judd, Kenny, and McClelland (2001), relies on a series of hypothesis tests about components of the mediation model and is not based on an estimate of or formal inference about the indirect effect. In this paper we recast Judd et al.’s approach in the path-analytic framework that is now commonly used in between-participant mediation analysis. By so doing, it is apparent how to estimate the indirect effect of a within-participant manipulation on some outcome through a mediator as the product of paths of influence. This path analytic approach eliminates the need for discrete hypothesis tests about components of the model to support a claim of mediation, as Judd et al’s method requires, because it relies only on an inference about the product of paths— the indirect effect. We generalize methods of inference for the indirect effect widely used in between-participant designs to this within-participant version of mediation analysis, including bootstrap confidence intervals and Monte Carlo confidence intervals. Using this path analytic approach, we extend the method to models with multiple mediators operating in parallel and serially and discuss the comparison of indirect effects in these more complex models. We offer macros and code for SPSS, SAS, and Mplus that conduct these analyses.

Get full-text (via PubEx)