Software models: A Bayesian approach to parameter estimation in the Jelenski-Moranda software reliability model

Maximum likelihood estimation procedures for the Jelinski-Moranda software reliability model often give misleading answers. A reparameterization and a Bayesian analysis eliminate some of the problems incurred by MLE methods and often give better predictions on sets of real and simulated data. Practical difficulties in estimating the initial number of errors N and the failure rate of each error phi by the method of maximum likelihood are: N, the MLE of N, is occasionally infinite (i.e., the routines for calculating N and phi do not converge). It is shown that N is finite sub i only if the regression line of the interevent times t sub i vs. i has positive slope. A serious problem is that often N approximates n, the sample size, and sometimes N = n. Thus the MLE predicts that the program is perfect even when it is far from being so. Only when almost all failures have been removed can N and phi be trusted near the end of debugging

A Collective Model of Female Labor Supply : Do Distribution Factors Matter in the Egyptian Case ?

This paper examines the intrahousehold ressource allocation in Egyptian married couples and its impact on females labor supply. Using data from the Egyptian Labor market and Panel Survey of 2006, we estimate a discrete-choice model for female labor supply within a collective framework. The economic model incorporates the possibility of non-participation for females which represents the working situation of more than 70 percent of Egyptian married women. The originality of this paper consists on testing new distribution factors, i.e., a set of exogenous variables which influence the intrahousehold allocation of resources without affecting preferences or the budget constraint. The latter are variables related to the marriage market, gender attitudes, domestic violence, direct access to the household income and participation in household decision making. Indentification of the model relies on the assumption that only some parameters of the utility function are identical for single and married females. We find significant relations between females bargaining power and labor supply decisions. This study's results has important policy implications.Collective model, labour supply, distribution factors, maximum simulated likelihood, Egypt.

Why do women's wages increase so slowly throughout their career? A dynamic model of statistical discrimination

The aim of this paper is to explain the growing wage differentials between men and womenduring their working careers. We provide a dynamic model of statistical discrimination, whichintegrates specific human capital decisions: on-the-job training investment and wages areendogenously determined. We reveal a small wage differential at the beginning of women'scareer, followed by a larger wage differential; this is partly due to a lower level of human capitalinvestment by women and partly because firms smooth training costs between different periods.Statistical discrimination, careers, male/female differentials, gender wage gap, specific human capital.

A Bayesian modification to the Jelinski-Moranda software reliability growth model

The Jelinski-Moranda (JM) model for software reliability was examined. It is suggested that a major reason for the poor results given by this model is the poor performance of the maximum likelihood method (ML) of parameter estimation. A reparameterization and Bayesian analysis, involving a slight modelling change, are proposed. It is shown that this new Bayesian-Jelinski-Moranda model (BJM) is mathematically quite tractable, and several metrics of interest to practitioners are obtained. The BJM and JM models are compared by using several sets of real software failure data collected and in all cases the BJM model gives superior reliability predictions. A change in the assumption which underlay both models to present the debugging process more accurately is discussed

Completely monotone regression estimates of software failure rates

A method for estimating the present failure rate of a program is presented. A crude nonparameter estimate of the failure rate function is obtained from past failure times. This estimate is then smoothed by fitting a completely monotonic function, which is the solution of a quadratic programming problem. The value of the smoothed function at present time is used as the estimate of present failure rate. Results of a Monte Carlo study of performance are given

A nonparametric software reliability growth model

Miller and Sofer have presented a nonparametric method for estimating the failure rate of a software program. The method is based on the complete monotonicity property of the failure rate function, and uses a regression approach to obtain estimates of the current software failure rate. This completely monotone software model is extended. It is shown how it can also provide long-range predictions of future reliability growth. Preliminary testing indicates that the method is competitive with parametric approaches, while being more robust

How Do Spouses Share their Full Income ? Identification of the Sharing Rule Using Self-Reported Income

The paper applies the collective model to the analysis of intra-household inequality using self-reported income scales. Starting from a collective model including household production, our key assumption is that the income level that household members report corresponds to their true income sharing. Using Russian data (Rounds V to VIII of the Russian Longitudinal Monitoring Survey), we apply the results for couples who report the same level of income to identify the sharing rule for the whole sample. This method allows us to obtain not only the derivatives, but also the sharing rule itself. From simulations for an average couple with one child living in the Urals, we find that a full income share of 45% is allocated to the wife.Collective model, within-household income comparisons, subjective data, Russia, sharing rule.

Control Function Assisted IPW Estimation with a Secondary Outcome in Case-Control Studies

Case-control studies are designed towards studying associations between risk factors and a single, primary outcome. Information about additional, secondary outcomes is also collected, but association studies targeting such secondary outcomes should account for the case-control sampling scheme, or otherwise results may be biased. Often, one uses inverse probability weighted (IPW) estimators to estimate population effects in such studies. However, these estimators are inefficient relative to estimators that make additional assumptions about the data generating mechanism. We propose a class of estimators for the effect of risk factors on a secondary outcome in case-control studies, when the mean is modeled using either the identity or the log link. The proposed estimator combines IPW with a mean zero control function that depends explicitly on a model for the primary disease outcome. The efficient estimator in our class of estimators reduces to standard IPW when the model for the primary disease outcome is unrestricted, and is more efficient than standard IPW when the model is either parametric or semiparametric

Household Division of Labor : Is There Any Escape From Traditional Gender Roles ?

The effects of women's strong investments in career and their relative positions on the household division of labor, particularly the share of male partners in household work, constitute important but somehow unaddressed issues. We use the French Time Use Survey, focusing on couples where both partners participate in the labor market, to build indicators of strong female investment in career, and look into the possible effect on the gender division of labor, particularly the male share of household work. We show that though a better relative position of the woman in the labor market increases her husband's share of household work, there is no role reversal in the division of labor.Household work, labor market, gender.