This paper investigates the potential of a cellular automata (CA) model based on logistic regression (logit) and Markov Chain Monte Carlo (MCMC) to simulate the dynamics of urban growth. The model assesses urbanization likelihood based on (i) a set of urban development driving forces (calibrated based on logit) and (ii) the land-use of neighboring cells (calibrated based on MCMC). An innovative...

One of the challenging issues for investors and professionals is appropriate models to evaluate financial situation of the firms. In this regard, many models have been extracted by researchers using different financial ratios to resolve these issues. However, choosing a model based on the conditions and users’ needs is complex. The main objective of this study is to identify the effect of conti...

The study analyzed farm households’ access and utilization of government health facilities in Kogi State, Nigeria. Specifically, it described the socioeconomic characteristics of farm households, determined the level of accessibility to health facilities by farm households, and determined the factors that drive farm households’ utilization of government health facilities. A two staged random sa...

Latent class models offer an alternative perspective to the popular mixed logit form, replacing the continuous distribution with a discrete distribution in which preference heterogeneity is captured by membership of distinct classes of utility description. Within each class, preference homogeneity is usually assumed (i.e., fixed parameters), although interactions with observed contextual effect...

BACKGROUND In biomedical research, response variables are often encountered which have bounded support on the open unit interval--(0,1). Traditionally, researchers have attempted to estimate covariate effects on these types of response data using linear regression. Alternative modelling strategies may include: beta regression, variable-dispersion beta regression, and fractional logit regression...

The distribution of the value of travel time savings (VTTS) is investigated employing nonparametric techniques on a large, high quality data set. When background variables are not included in the model it is found that the right tail of the distribution is not observed and hence the mean VTTS cannot be evaluated. This conclusion changes when background variables are introduced into a semiparame...

The paper proposes a new estimator for the fixed effects ordered logit model. In contrast to existing methods, the new procedure allows estimating the thresholds. The empirical relevance and simplicity of implementation is illustrated in an application to the effect of unemployment on life satisfaction.

This talk considers the special case of binomial data where repeated measurements are available for identical covariate patterns. Our method is based on various Bayesian approaches for estimating binary logit models. To carry out MCMC sampling with data augmentation, logit models are rewritten as random utility models (RUM) or difference RUM (dRUM). Following earlier papers (Frühwirth-Schnatter...