Recently, a novelty multinomial logistic regression method where the initial covariate space is increased by adding the nonlinear transformations of the input variables given by Gaussian Radial Basis Functions (RBFs) obtained by an evolutionary algorithm was proposed. However, there still exist some problems with the standard Gaussian RBF, for example, the approximation of constant valued funct...

A new logistic model for bacterial growth was developed in this study. The model, which is based on the logistic model, contains an additional term for expression of the very low rate of growth during a lag phase, in its differential equation. The model successfully described sigmoidal growth curves of Escherichia coli at various initial cell concentrations and constant temperatures. The model ...

We know that the marginals in a multinomial distribution are binomial variates exhibiting a negative correlation. But we can construct two linear combinations of such marginals in such a way to obtain a positive correlation. We discuss the restrictions that are to be imposed on the parameters of the given marginals to accomplish such a result. Next we discuss the regression function, showing th...

throughout the current study, the appropriate function for a description of egg production curve in a commercial broiler dam line was determined through fittings of a number of six mathematical models, namely: incomplete gamma function (wm): modified incomplete gamma function (mwm): compartmental function (cm): modified compartmental function )mcm): polynomial regression function of ali and sch...

In this note we consider unimodality problems of sequences of multinomial coefficients and symmetric functions. The results presented here generalize our early results for binomial coefficients. We also give an answer to a question of Sagan about strong q-log-concavity of certain sequences of symmetric functions, which can unify many known results for q-binomial coefficients and q-Stirling numb...

In this paper, we discuss the estimation of the parameter function for a functional logistic regression model in the presence of outliers. We consider ways that allow for the parameter estimator to be resistant to outliers, in addition to minimizing multicollinearity and reducing the high dimensionality which is inherent with functional data. To achieve this, the functional covariates and funct...