Motivation with regard to attitudes toward procreation among married women

The results of a sample survey on attitudes toward reproduction in Poland are presented in this two-part article. The survey, which was conducted by the Central Statistical Office in 1977, covered 9,799 women up to age 45. The women surveyed are divided into three main groups, consisting of those with positive, conditional, and negative attitudes toward having more children. The attitudes and characteristics of the women are analyzed.     

Procreative attitudes of newly married couples

Results are presented from a 1985 survey conducted among newly married couples in Poland concerning ideal and planned number of children. Both husbands and wives participated in the survey. Comparisons are made with results from a previous survey undertaken in 1975.     

Models of procreative behavior based on the concept of the life cycle

This is the first in a planned series of papers applying path analysis methods to the study of reproductive behavior in rural areas in Poland. Factors considered include total number of births, birth intervals, birth control and abortion, and future fertility intentions. The objective is to examine how the fertility of rural women is affected by various social and economic factors. (SUMMARY IN ENG)     

Men matter more: the social class identity of married British women, 1985–1991

Summary.  We investigate the class identity of married women as it relates to their own and their husband's class position. Whereas previous workers have attempted to test whether identity depends solely on the husband's position, not at all on the husband's position or equally on the husband's and wife's position, leaving out all intermediate cases, we estimate new diagonal reference models that quantify the relative weight of each partner's class position on their own class identity. In previous literature, it was also argued that women who work full time should be more likely to adopt a sharing model than other women and in some cases these different types of women were compared. We move beyond this simple dichotomy and more systematically formulate hypotheses about the conditions under which women attach more or less weight to their own class position and less or more weight respectively to that of their husbands. To test these hypotheses, we consider models where the weights are allowed to depend on characteristics of each partner and the couple. Using the British Social Attitudes Survey data for 1985–1991, we find that, when the husband's commitment to the labour force exceeds that of the wife, the husband's weight exceeds the wife's weight but, when the wife's commitment exceeds that of the husband's, the weights are approximately equal. We also find (unexpectedly) that women who hold higher positions than their husbands attach more weight to their husband's position than to their own position.     

Estimation under length-bias and right-censoring: an application to unemployment duration analysis for married women

In this work we analyse unemployment duration for married women in Spain, using the Labour Force Survey (LFS) of the Spanish Institute for Statistics, 1987-1997. Consistent non-parametric estimation of the unemployment survival function is provided. Since the available data are length- biased, a suitable correction of the Kaplan-Meier product-limit estimator is motivated and used for the referred analysis. The accuracy of parametric models is checked by means of goodness-of-fit plots--a graphical tool that requires preliminary estimation of the survival. Structural features of the associated hazard (as monotonicity and unimodality) are explored.     

On the determination of mixing density in reliability studies

In reliability studies the three quantities (1) the survival function, (2) the failure rate and (3) the mean residual life function are all equivalent in the sense that given one of them, the other two can be determined. In this paper we have considered the class of exponential type distributions and studied its mixture. Given any one of the above mentioned three quantities of the mixture a method is developed for determining the mixing density. Some examples are provided as illustrations. Some well known results follow trivially.     

On the relative behavior of estimators of reliability/survivability

Based on a decomposition of mean absolute error, a twofold technique is introduced whereby a pairwise comparison of point estimators of reliability/survivability can be made. Given two such estimators, the method examines (a) the “odds” in favor of one of the estimators being closer to the true value than is the other and (b) each estimator’s average closeness to the true value not only when it is closer than is the other but also when it is not. Joint consideration of these concepts is shown to form a basis for determining which of the two estimators is preferred in a given situation. An application of the theory is made by comparing the maximum likelihood and minimum variance unbiased estimators of reliability/survivability in the exponential failure model.     

On parameter estimation of software reliability models

Most software reliability models use the maximum likelihood method to estimate the parameters of the model. The maximum likelihood method assumes that the inter-failure time distributions contribute equally to the likelihood function. Since software reliability is expected to exhibit growth, a weighted likelihood function that gives higher weights to latter inter-failure times compared to earlier ones is suggested. The accuracy of the predictions obtained using the weighted likelihood method is compared with the predictions obtained when the parameters are estimated by the maximum likelihood method on three real datasets. A simulation study is also conducted.     

On improving the robustness and reliability of Rao's score test

The results of misspecification tests, based on Rao's score principle, are now routinely reported in applied econometric work. This paper draws together some important recent results which are designed to improve: (a) the robustness of standard score tests; and (b) the reliability of the asymptotic approximations used for inferential purposes. The discussion of robustness includes (i) parametric, (ii) distributional, and (iii) higher-order moment robustness. The issue of finite sample reliability focuses on controlling the size of the score test using (i) different variance estimators in conjunction with standard asymptotic theory, (ii) finite sample corrections obtainable from higher-order asymptotic analysis, and (iii) bootstrap procedures.     

On some reliability aspects of Pearson family of distributions

We characterize the Pearson family of distributions by finding a relationship between the failure rate and the higher order moments of residual life. We also present a characterization theorem of IFR(DFR) class of distributions in the Pearson family.     

On the mean residual life function of a mixture in reliability studies

In reliability studies, the additional life time given that a component has survived until time t is called the Mean residual life function (MRLF). This MRLF determines the distribution function uniquely. There exist many life testing situations which can be best described as mixtures of distributions. In this paper we have considered the general MRLF and have developed a method of obtaining the mixing distribution when the original distribution is exponential. Some examples are discussed, in one of which Morrison’s (1978) result is obtained as a special case.     

On reliability estimation based on fuzzy lifetime data

Real lifetime data are never precise numbers but more or less non-precise, also called fuzzy. This kind of imprecision is connected with all measurement results of continuous variables, therefore also with time observations. Imprecision is different from errors and variability. Therefore estimation methods for reliability characteristics have to be adapted to the situation of fuzzy lifetimes in order to obtain realistic results.     

On some reliability measures and their stochastic orderings for the Topp-Leone distribution

Topp-Leone distribution is a continuous unimodal distribution with bounded support (recently rediscovered) which is useful for modelling life-time phenomena. In this paper we study some reliability measures of this distribution such as the hazard rate, mean residual life, reversed hazard rate, expected inactivity time, and their stochastic orderings.     

Time use of married couples: Bayesian approach

ABSTRACT

The living hours data of individuals' time spent on daily activities are compositional and include many zeros because individuals do not pursue all activities every day. Thus, we should exercise caution in using such data for empirical analyses. The Bayesian method offers several advantages in analyzing compositional data. In this study, we analyze the time allocation of Japanese married couples using the Bayesian model. Based on the Bayes factors, we compare models that consider and do not consider the correlations between married couples' time use data. The model that considers the correlation shows superior performance. We show that the Bayesian method can adequately take into account the correlations of wives' and husbands' living hours, facilitating the calculation of partial effects that their activities' variables have on living hours. The partial effects of the model that considers the correlations between the couples' time use are easily calculated from the posterior results.     

On estimating the reliability in a multicomponent stress-strength model based on Chen distribution

Abstract

In this article, we obtain point and interval estimates of multicomponent stress-strength reliability model of an s-out-of-j system using classical and Bayesian approaches by assuming both stress and strength variables follow a Chen distribution with a common shape parameter which may be known or unknown. The uniformly minimum variance unbiased estimator of reliability is obtained analytically when the common parameter is known. The behavior of proposed reliability estimates is studied using the estimated risks through Monte Carlo simulations and comments are obtained. Finally, a data set is analyzed for illustrative purposes.     

Testing the reliability of forecasting systems

The problem of statistically evaluating forecasting systems is revisited. The forecaster claims the forecasts to exhibit a certain nominal statistical behaviour; for instance, the forecasts provide the expected value (or certain quantiles) of the verification, conditional on the information available at forecast time. Forecasting systems that indeed exhibit the nominal behaviour are referred to as reliable. Statistical tests for reliability are presented (based on an archive of verification–forecast pairs). As noted previously, devising such tests is encumbered by the fact that the dependence structure of the verification–forecast pairs is not known in general. Ignoring this dependence though might lead to incorrect tests and too-frequent rejection of forecasting systems that are actually reliable. On the other hand, reliability typically implies that the forecast provides information about the dependence structure, and using this in conjunction with judicious choices of the test statistic, rigorous results on the asymptotic distribution of the test statistic are obtained. These results are used to test for reliability under minimal additional assumptions on the statistical properties of the verification–forecast pairs. Applications to environmental forecasts are discussed. A python implementation of the discussed methods is available online.     

Bayes estimators of the reliability of the logistic distribution

Bayes estimators of the reliability function of the logistic distribution are obtained using the methods of Lindley (1980) and Tierney & Kadane (1986). Squared-error and log-odds squared-error loss functions are used. A numerical example is presented. Comparisons are made between these two procedures, based on a Monte Carlo simulation study.     

Estimation of system reliability

In this paper, we estimate the reliability of a system with k components. The system functions when at least s (1≤s≤k) components survive a common random stress. We assume that the strengths of these k components are subjected to a common stress which is independent of the strengths of these k components. If (X ₁,X ₂,…,X _k ) are strengths of k components subjected to a common stress (Y), then the reliability of the system or system reliability is given byR=P[Y<X _(k−s+1)] whereX _(k−s+1) is (k−s+1)-th order statistic of (X ₁,…,X _k ). We estimate R when (X ₁,…,X _k ) follow an absolutely continuous multivariate exponential (ACMVE) distribution of Hanagal (1993) which is the submodel of Block (1975) and Y follows an independent exponential distribution. We also obtain the asymptotic normal (AN) distribution of the proposed estimator.     

Appraisal of the reliability of infant mortality data

The authors evaluate the reliability of infant mortality data in the USSR. Various indirect estimation methods are assessed. The focus is on the Bourgeois-Pichat method, which they apply to available statistics for individual Union republics. They conclude that this method can be used with data sets of varying degrees of reliability.