In this article, multiple-product PVRP with pickup and delivery that is used widely in goods distribution or other service companies, especially by railways, was introduced. A mathematical formulation was provided for this problem. Each product had a set of vehicles which could carry the product and pickup and delivery could simultaneously occur. To solve the problem, two meta-heuristic methods...

The market basket data in the form of a binary user-item matrix or a binary item-user matrix can be modelled as a binary classification problem. The binary logistic regression approach tackles the binary classification problem, where principal components are predictor variables. If users or items are sparse in the training data, the binary classification problem can be considered as a cold-star...

Binary toxin CDT or its genes have been identified in some strains of Clostridium difficile that also produce the large clostridial toxins, toxins A and B (A+B+CDT+), including a newly recognized epidemic strain in the United States and Canada. To study the effects of binary toxin alone, we characterized 4 binary toxin CDT-positive only (A-B-CDT+) C. difficile strains. Unlike other clostridial ...

In this paper, we consider binary response correlated random coefficient (CRC) panel data models which are frequently used in the analysis of treatment effects and demand of products. We focus on the nonparametric identification and estimation of panel data models under unobserved heterogeneity which is captured by random coefficients and when these random coefficients are correlated with regre...

In clinical research, in addition to continuous responses, primary clinical endpoints for assessment of efficacy and safety of a drug product under investigation could be binary responses. For example, in cancer trials, patients’ clinical reaction to the treatment is often classified as response (e.g., complete response or partial response) or nonresponse. Based on these binary responses, the p...

A Semiparametric Model for Binary Response and Continuous Outcomes Under Index Heteroscedasticity This paper formulates a likelihood-based estimator for a double index, semiparametric binary response equation. A novel feature of this estimator is that it is based on density estimation under local smoothing. While the proofs differ from those based on alternative density estimators, the finite s...

binary decision diagram (bdd) is a data structure proved to be compact in representation and efficient in manipulation of boolean formulas. using binary decision diagram in network reliability analysis has already been investigated by some researchers. in this paper we show how an exact algorithm for network reliability can be improved and implemented efficiently by using cudd - colorado univer...

in this paper, we consider an arbitrary binary polynomial sequence {a_n} and then give a lower triangular matrix representation of this sequence. as main result, we obtain a factorization of the in nite generalized pascal matrix in terms of this new matrix, using a riordan group approach. further some interesting results and applications are derived.

Sufficient dimension reduction is popular for reducing data dimensionality without stringent model assumptions. However, most existing methods may work poorly for binary classification. For example, sliced inverse regression (Li, 1991) can estimate at most one direction if the response is binary. In this paper we propose principal weighted support vector machines, a unified framework for linear...