conclusions although ceiling effects should be considered for rehabilitation targets, the two-factor model of fim (motor and cognitive independence) has an eligible fitness for iranian patients with tbi. results the results of this study showed that the floor effect was not observed; however, ceiling effects were observed for the fim total score and its subscales. the confirmatory factor analys...

There are often two types of correlations in multivariate spatial data: correlations between variables measured at the same locations, and correlations of each variable across the locations. We hypothesize that these two types of correlations are caused by a common spatially correlated underlying factor. Under this hypothesis, we propose a generalized common spatial factor model. The parameters...

This paper provides a unified setting for factor models applied to panels of qualitative observations. This setting includes as special cases the single risk factor model and its multiple factor extensions used in credit risk analysis, the stochastic migration models used for rating dynamics, and the factor models for prospective mortality tables. We consider the behavior of these models when t...

The five-factor model of personality (FFM) is a set of five broad trait dimensions or domains, often referred to as the “Big Five”: Extraversion, Agreeableness, Conscientiousness, Neuroticism (sometimes named by its polar opposite, Emotional Stability), and Openness to Experience (sometimes named Intellect). Highly extraverted individuals are assertive and sociable, rather than quiet and reserv...

this study aims to evaluate effects of two downscaling methods; change-factor and statistical downscaling on therunoff of the azam-harat river located at yazd province (with an arid climate) of iran, under the a2 emission scenariofor the period of 2010-2039. for this purpose, cgcm3-ar4 model; a rainfall-runoff conceptual model, ihacres; twodownscaling models, change factor and lars-wg were appl...

We propose a nonparametric Bayesian factor regression model that accounts for uncertainty in the number of factors, and the relationship between factors. To accomplish this, we propose a sparse variant of the Indian Buffet Process and couple this with a hierarchical model over factors, based on Kingman’s coalescent. We apply this model to two problems (factor analysis and factor regression) in ...

SPENCER ERIC HAYS: A Functional Dynamic Factor Model. (Under the direction of Haipeng Shen.) Functional data analysis is a burgeoning area in statistics. However, much of the literature to date deals primarily with methods for collections of independent functional observations, which are not well suited to application with time series of curves. In this paper, a functional time series model is ...

Wind loads on structures under the buffeting action of wind gusts have traditionally been treated by the ‘‘gust loading factor’’ (GLF) method in most major codes and standards around the world. In this scheme, the equivalent static wind loading used for design is equal to the mean wind force multiplied by the GLF. Although the traditional GLF method ensures an accurate estimation of the displac...

The Gaussian factor copula model is the market standard model for multi-name credit derivatives. Its main drawback is that factor copula models exhibit correlation smiles when calibrating against market tranche quotes. To overcome the calibration deficiency, we introduce a multi-period factor copula model by chaining one-period factor copula models. The correlation coefficients in our model are...