1,721,020 research outputs found
Editorial for the special issue on: Statistics with unobservable variables - SUNOVA 2012
No full textDeveloping a composite index by using spatial latent modelling based on information theoretic estimatio
No full textThe focus of this paper is on spatial structural equation models (S-SEM) also extended to a Panel data framework. More specifically, our objective is to introduce a generalized maximum entropy formulation for the class of S-SEM with the aim of developing a composite index. We present an application of the method to real data finalized to investigatedynamicsandcomplexinteractionsbetweensomeselecteddimensionsthatrepresentthe mainmeasuresofintangibleassetsforapanelofOECDcountriesovertheperiod1998–2008
Editorial for the special issue on: Sunova shape 2014
No full textStatistical methods, models and applications that assume the existence of not directly observable variables are today extensively used in every research area. This special issue, inspired by the workshop "statistics with UNOb-servable Variables &Statistical models for human perception and evalua-tion" (Sunova &Shape 2014), which was held at the Department of eco-nomics and business of the university of Brescia (Italy) as part of the ac-tivities of the DMS statlab statistical laboratory "data methods and Systems" in October 21, 2014, highlights the opportunities offered by some of the most advanced statistical approaches based on unobservable variables
A job satisfaction structural equation model obtained combining Rasch Analysis and Generalized Maximum Entropy estimation
No full textW
Streaming generalized cross entropy
No full textWe propose a new method to combine adaptive processes with a class of entropy estimators for the case of streams of data. Starting from a first estimation obtained from a batch of initial data, model parameters are estimated at each step by combining the prior knowledge with the new observation (or a block of observations). This allows to extend the maximum entropy technique to a dynamical setting, also distinguishing between entropic contributions of the signal and the error. Furthermore, it provides a suitable approximation of standard GME problems when the exacted solutions are hard to evaluate. We test this method by performing numerical simulations at various sample sizes and batch dimensions. Moreover, we extend this analysis exploring intermediate cases between streaming GCE and standard GCE, i.e., considering blocks of observations of different sizes to update the estimates, and incorporating collinearity effects as well. The role of time in the balance between entropic contributions of signal and errors is further explored considering a variation of the Streaming GCE algorithm, namely Weighted Streaming GCE. Finally, we discuss the results: In particular, we highlight the main characteristics of this method, the range of application, and future perspectives
NON-SYMMETRICAL CORRESPONDENCE ANALYSIS TO EVALUATE HOW AGE INFLUENCES THE ADDICTION DISCOURSES
No full textMultivariate statistical approaches for the customer satisfaction into transportation sector
Full text linkThe aim of this paper is to study the effect of the dimensions of the
transportation service on the Passenger Satisfaction (PS) taking into
account the spatial effect due to the interaction across spatial units and
spatial heterogeneity. The relationships between the service dimensions and PS are formalized by a Structural Equation Model (SEM) based on the Partial Least Squares (PLS) estimation method which includes in the measurement model the spatial effects. Moreover, to get a ‘true’ measure of satisfaction, the rating scale model is proposed
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