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Manisha Pal

Researcher at University of Calcutta

Publications -  86
Citations -  953

Manisha Pal is an academic researcher from University of Calcutta. The author has contributed to research in topics: Optimal design & Mixture model. The author has an hindex of 15, co-authored 84 publications receiving 861 citations.

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Parameter estimation in linear and quadratic mixture models: a review *

TL;DR: In this article, the problems of unbiased estimation of parameters in linear and quadratic mixture models have been revisited and some generalizations of the axial designs have been proposed and a comparative study of these designs, in respect of their information matrices, has been considered.

A Periodic Review Inventory Model for Deteriorating Items with Price Dependent Demand and Partial Delay in Payment under Inflation

TL;DR: In this paper, a period review inventory model for deteriorating items allowing shortage and under price inflation is proposed, where demand during a reorder interval is assumed to be price dependent and the inventory manager has the option to pay his dues in two installments within a re-order interval.
Book ChapterDOI

Optimal Mixture Designs for Estimation of Natural Parameters in Other Mixture Models

TL;DR: This chapter focuses on finding optimum mixture designs for the estimation of natural parameters of models other than that of Scheffe viz., Becker’s models, Darroch–Waller [D–W] model and Log-contrast model.
Book ChapterDOI

More on Estimation of Optimum Mixture in Scheffé’s Quadratic Model

TL;DR: In this paper, the problem of finding optimum mixture designs under deficiency and minimax criteria is addressed, and Kiefer's equivalence theorem plays a key role in identifying the designs.
Journal ArticleDOI

Maximin designs for the detection of synergistic effects

TL;DR: In this article, the authors attempt to find the optimum designs for testing the presence of synergistic effects in a mixture model using the maximin criterion, which is the same as in this paper.