this study predicts corporate bankruptcy five years before its occurrence using financial ratios introduced in altman’s z-score model and current ratio. three estimation methods namely; liner probability, logit and probit models have chosen for model estimation. the sample contains 134 companies in tehran stock exchange during 2003. the precision of prediction of the estimated models for the ma...

Land-use change models are used to explore the dynamics and drivers of land-use/landcover change and to inform policies affecting such change. A broad array of applications and modeling methods are available and each type has certain advantages and disadvantages depending on the objective of the research. This work presents an approach combining cellular automata (CA) model and supported vector...

In clinical research, suitable visualization techniques of data after statistical analysis are crucial for the researches' and physicians' understanding. Common statistical techniques to analyze data in clinical research are logistic regression models. Among these, the application of binary logistic regression analysis (LRA) has greatly increased during past years, due to its diagnostic accurac...

Empirical studies on household car ownership have used two types of discrete choice modelling structures, the ordered and the unordered. In ordered structures such as the ordered logit and ordered probit models, the choice of the number of household-vehicles arises from a uni-dimensional latent index that reflects the propensity of a household to own vehicles. Unordered response models, on the ...

This article contains the data on farmers' determinants of binary choices for manure use (i.e., manure is used or unused) and fertiliser use (i.e., fertiliser is used or unused) at their fields in semi-arid northern Ethiopian Rift Valley. The data includes (i) a schematic diagram that represents local farmers' distinctions of the crop field types in terms of the distance from their houses and s...

Weight of evidence (WOE) coding of a nominal or discrete variable is widely used when preparing predictors for usage in binary logistic regression models. When using WOE coding, an important preliminary step is binning of the levels of the predictor to achieve parsimony without giving up predictive power. These concepts of WOE and binning are extended to ordinal logistic regression in the case ...

This chapter examines different models commonly used to model probabilistic choice, such as eg the choice of one type of transportation from among many choices available to the consumer. Section 1 discusses derivation and limitations of conditional logit models. Section 2 discusses probit models and Section 3 discusses the nested logit (generalized extreme value models), which address some of t...