Recent trends in modeling of deteriorating inventory

4. Modelling Survival Data in Medical Research

This paper presents a complete and up-to-date survey of published inventory literature for the deteriorating (decaying) inventory models. More specifically, those papers are addressed that consider the effect of deterioration as a function of the on-hand level of inventory. The basic features, extensions and generalization of various models are discussed. A classification scheme is presented along with suggestions for future research.

https://link.springer.com/content/pdf/10.1057%2Fjors.1991.4.pdf

Survey of Literature on Continuously Deteriorating Inventory Models

Infertility and problems of impaired fecundity have been a concern through ages and is also a significant clinical problem today, which affects 8-12% of couples worldwide. Of all infertility cases, approximately 40-50% is due to "male factor" infertility and as many as 2% of all men will exhibit suboptimal sperm parameters. It may be one or a combination of low sperm concentration, poor sperm motility, or abnormal morphology. The rates of infertility in less industrialized nations are markedly higher and infectious diseases are responsible for a greater proportion of infertility. The present literature will help in knowing the trends of male factor infertility in developing nations like India and to find out in future, various factors that may be responsible for male infertility.

Trends of male factor infertility, an important cause of infertility: A review of literature.

Approximately 10 to 15% of couples are impacted by infertility. Recently, the pivotal role that lifestyle factors play in the development of infertility has generated a considerable amount of interest. Lifestyle factors are the modifiable habits and ways of life that can greatly influence overall health and well-being, including fertility. Many lifestyle factors such as the age at which to start a family, nutrition, weight, exercise, psychological stress, environmental and occupational exposures, and others can have substantial effects on fertility; lifestyle factors such as cigarette smoking, illicit drug use, and alcohol and caffeine consumption can negatively influence fertility while others such as preventative care may be beneficial. The present literature review encompasses multiple lifestyle factors and places infertility in context for the couple by focusing on both males and females; it aims to identify the roles that lifestyle factors play in determining reproductive status. The growing interest and amount of research in this field have made it evident that lifestyle factors have a significant impact on fertility.

/pdf/lifestyle-factors-and-reproductive-health-taking-control-of-ob45s39pgz.pdf

Lifestyle factors and reproductive health: taking control of your fertility

This chapter examines the optimum designs for estimating the optimum mixing proportions in Scheffe’s quadratic mixture model with respect to the A-optimality criterion. By optimum mixing proportion, we refer to the one that maximizes the mean response. Since the dispersion matrix of the estimate depends on the unknown model parameters, a pseudo-Bayesian approach is used in defining the optimality criterion. The optimum designs under this criterion have been obtained for two- and three-component mixtures. Further, using Kiefer’s equivalence theorem, it has been shown that under invariant assumption on prior moments, the optimum design for a \(q\)-component mixture is a \((q, 2)\) simplex lattice design for \(q = 3, 4.\)

Optimal Designs for Estimation of Optimum Mixture in Scheffé’s Quadratic Model

In this chapter, we review the optimality results for the estimation of parameters and subset of parameters of the Scheffe’s mixture models while the factor space is the entire simplex, ie, while we are in the framework of an unconstrained factor space  Though most of the results are related to quadratic model, optimality results for linear- and higher-degree polynomials are also discussed Kiefer’s equivalence theorem plays an important role in characterizing optimum designs It has been observed that the support points of an optimum design under different optimality criteria belong to the subclass of union of barycenters

Optimal Mixture Designs for Estimation of Natural Parameters in Scheffé’s Models

The paper studies the log-logistic class of dose-response bioassay models in the binomial set-up. The dose is identified by the potency adjusted mixing proportions of two similar compounds. Models for both absence and presence of interaction between the compounds have been considered. The aim is to investigate the D- and Ds- optimal mixture designs for the estimation of the full set of parameters or for the estimation of potency for a best guess of the parameter values. We also indicate how to find the optimal design to estimate the mixing proportions at which the probability of success attains a given value in the absence of interaction effect.

Optimum mixture designs for the log-logistic dose–response model with mixture of two similar compounds

The present study focuses on the problems of parameter estimation and growth prediction in a quadratic growth model based on repeated measurements of growth, where the parameters in the model are assumed to be functions of ‘treatments’ which are treated as mixtures The study concentrates not only on the optimality aspects of designs for most efficient estimation of the parameters but also on optimal prediction of growth at designated time points

Growth Models for Repeated Measurement Mixture Experiments: Optimal Designs for Parameter Estimation and Growth Prediction

In this chapter, we present standard mixture models and standard mixture designs as generally applied to such models. These mixture models and mixture designs will occur throughout the monograph. Several generalizations of standard mixture designs are also discussed here. Estimability issues involving the model parameters are addressed at length. In the process, information matrices are worked out and their roles are emphasized. The concept of Loewner domination is also brought in.

Manisha Pal

Papers

Optimal Designs for Estimation of Optimum Mixture in Scheffé’s Quadratic Model

Optimal Mixture Designs for Estimation of Natural Parameters in Scheffé’s Models

Optimum mixture designs for the log-logistic dose–response model with mixture of two similar compounds

Growth Models for Repeated Measurement Mixture Experiments: Optimal Designs for Parameter Estimation and Growth Prediction

Parameter Estimation in Linear and Quadratic Mixture Models