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Contribuições à análise de outliers em modelos de equações estruturais; Contributions to the analysis of outliers in structural equation models

Bulhões, Rodrigo de Souza
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 10/05/2013 PT
Relevância na Pesquisa
76.12%
O Modelo de Equações Estruturais (MEE) é habitualmente ajustado para realizar uma análise confirmatória sobre as conjecturas de um pesquisador acerca do relacionamento entre as variáveis observadas e latentes de algum estudo. Na prática, a maneira mais recorrente de avaliar a qualidade das estimativas de um MEE é a partir de medidas que buscam mensurar o quanto a usual matriz de covariâncias clássicas ou ordinárias se distancia da matriz de covariâncias do modelo ajustado, ou a magnitude do afastamento entre as funções de discrepância do modelo hipotético e do modelo saturado. Entretanto, elas podem não captar problemas no ajuste quando há muitos parâmetros a estimar ou bastantes observações. A fim de detectar irregularidades no ajustamento resultantes do impacto provocado pela presença de outliers no conjunto de dados, este trabalho contemplou alguns indicadores conhecidos na literatura, como também considerou alterações no Índice da Qualidade do Ajuste (ou GFI, de Goodness-of-Fit Index) e no Índice Corrigido da Qualidade do Ajuste (ou AGFI, de Ajusted Goodness-of-Fit Index), ambos nas expressões para estimação de parâmetros pelo método de Máxima Verossimilhança, que consistiram em substituir a tradicional matriz de covariâncias pelas matrizes de covariâncias computadas com os seguintes estimadores: Elipsoide de Volume Mínimo...

Análise do impacto de perturbações sobre medidas de qualidade de ajuste para modelos de equações estruturais; Analysis of the impact of disturbances over the measures of goodness of fit for structural equation models

Brunelli, Renata Trevisan
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 11/05/2012 PT
Relevância na Pesquisa
96.09%
A Modelagem de Equações Estruturais (SEM, do inglês Structural Equation Modeling) é uma metodologia multivariada que permite estudar relações de causa/efeito e correlação entre um conjunto de variáveis (podendo ser elas observadas ou latentes), simultaneamente. A técnica vem se difundindo cada vez mais nos últimos anos, em diferentes áreas do conhecimento. Uma de suas principais aplicações é na conrmação de modelos teóricos propostos pelo pesquisador (Análise Fatorial Conrmatória). Existem diversas medidas sugeridas pela literatura que servem para avaliar o quão bom está o ajuste de um modelo de SEM. Entretanto, é escassa a quantidade de trabalhos na literatura que listem relações entre os valores de diferentes medidas com possíveis problemas na amostra e na especicação do modelo, isto é, informações a respeito de que possíveis problemas desta natureza impactam quais medidas (e quais não), e de que maneira. Tal informação é importante porque permite entender os motivos pelos quais um modelo pode estar sendo considerado mal-ajustado. O objetivo deste trabalho é investigar como diferentes perturbações na amostragem, especicação e estimação de um modelo de SEM podem impactar as medidas de qualidade de ajuste; e...

Parametric VaR with goodness-of-fit tests based on EDF statistics for extreme returns

Moralles, Herick Fernando; Rebelatto, Daisy Aparecida do Nascimento; Sartoris, Alexandre
Fonte: Universidade Estadual Paulista Publicador: Universidade Estadual Paulista
Tipo: Artigo de Revista Científica Formato: 1648-1658
ENG
Relevância na Pesquisa
96.03%
Parametric VaR (Value-at-Risk) is widely used due to its simplicity and easy calculation. However, the normality assumption, often used in the estimation of the parametric VaR, does not provide satisfactory estimates for risk exposure. Therefore, this study suggests a method for computing the parametric VaR based on goodness-of-fit tests using the empirical distribution function (EDF) for extreme returns, and compares the feasibility of this method for the banking sector in an emerging market and in a developed one. The paper also discusses possible theoretical contributions in related fields like enterprise risk management (ERM). © 2013 Elsevier Ltd.

An Alternative Goodness-of-fit Test for Normality with Unknown Parameters

Shi, Weiling
Fonte: FIU Digital Commons Publicador: FIU Digital Commons
Tipo: Artigo de Revista Científica Formato: application/pdf
Relevância na Pesquisa
95.95%
Goodness-of-fit tests have been studied by many researchers. Among them, an alternative statistical test for uniformity was proposed by Chen and Ye (2009). The test was used by Xiong (2010) to test normality for the case that both location parameter and scale parameter of the normal distribution are known. The purpose of the present thesis is to extend the result to the case that the parameters are unknown. A table for the critical values of the test statistic is obtained using Monte Carlo simulation. The performance of the proposed test is compared with the Shapiro-Wilk test and the Kolmogorov-Smirnov test. Monte-Carlo simulation results show that proposed test performs better than the Kolmogorov-Smirnov test in many cases. The Shapiro Wilk test is still the most powerful test although in some cases the test proposed in the present research performs better.

Goodness of fit function in the frequency domain for robust calibration of microscopic traffic flow models

PUNZO VINCENZO; MONTANINO Marcello; CIUFFO BIAGIO
Fonte: Transportation Research Board of the National Academies Publicador: Transportation Research Board of the National Academies
Tipo: Contributions to Conferences Formato: Online
ENG
Relevância na Pesquisa
75.98%
In the field of traffic simulation, the calibration of uncertain inputs against real data is usually taken to cover both the epistemic uncertainty regarding the un-modeled details of the phenomena and the aleatory not predicted by the models. For this reason, model parameters are usually indirectly estimated within an optimization framework which tries to maximize the fit between real and simulated measures of the traffic system. This is the case, for example, of the calibration of car-following models’ parameters against vehicle trajectory data. Only recently, it has been proven that the capability of the optimization framework to provide the parameters’ values that allow the car-following model reproducing real trajectories at its best is strictly connected to the setting of the optimization framework itself. This, in particular, entails the necessity to carefully choose an appropriate combination of optimization algorithm and measure of goodness of fit (GOF). In this study, the authors focus attention on this latter issue. Specifically, it is claimed here that the commonly used GOFs are not able to capture the dynamics of the time-series which calibration is performed against. Therefore, a spectral analysis based approach to evaluate the overall performance of the simulation model in the objective function is proposed. The new measure of goodness of fit is tested in the calibration of the Intelligent Driver Model against synthetic and real trajectory data. Results with synthetic data...

Cox process goodness-of-fit test. A Matlab file.

Bouzas, Paula R.; Ruiz-Fuentes, Nuria
Fonte: Universidade de Granada Publicador: Universidade de Granada
Tipo: Pré-impressão
ENG
Relevância na Pesquisa
85.91%
The Cox Process (CP) models many real phenomena dealing with counting data. Having observed sample paths of a counting process in a discrete set of time points and assuming that the phenomenon can be modeled by a Cox process or compound Cox process, an important task is to decide if those paths fit a given model. A goodnes-of-fit test to assess the coherence of the new observed data with the given Cox process has been proposed by the authors, taking into account if the process is parametrically known or it has to be estimated. This paper deals with a computational tool to support the test.

Goodness of fit in models for mortality data

Camarda, Carlo Giovanni; Durbán, María
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: Trabalho em Andamento Formato: application/pdf
Publicado em /09/2008 ENG
Relevância na Pesquisa
95.96%
Mortality data on an aggregate level are characterized by very large sample sizes. For this reason, uninformative outcomes are evident in common Goodness-of-Fit measures. In this paper we propose a new measure that allows comparison of different mortality models even for large sample sizes. Particularly, we develop a measure which uses a null model specifically designed for mortality data. Several simulation studies and actual applications will demonstrate the performances of this new measure with special emphasis on demographic models and Pspline approach.

Asymptotic properties of a goodness-of-fit test based on maximum correlations

Grané, Aurea; Tchirina, Anna V.
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: Trabalho em Andamento Formato: application/pdf
Publicado em /09/2008 ENG
Relevância na Pesquisa
95.95%
We study the efficiency properties of the goodness-of-fit test based on the Qn statistic introduced in Fortiana and Grané (2003) using the concepts of Bahadur asymptotic relative efficiency and Bahadur asymptotic optimality. We compare the test based on this statistic with those based on the Kolmogorov-Smirnov, the Cramér-von Mises and the Anderson-Darling statistics. We also describe the distribution families for which the test based on Qn is asymptotically optimal in the Bahadur sense and, as an application, we use this test to detect the presence of hidden periodicities in a stationary time series.

Goodness of fit tests in random coefficient regression models

Delicado, Pedro; Romo, Juan
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: Trabalho em Andamento Formato: application/pdf
Publicado em /12/1994 ENG
Relevância na Pesquisa
95.96%
Random coefficient regressions have been applied in a wide range of fields, from biology to economics, and constitute a common frame for several important statistical models. A nonparametric approach to inference in random coefficient models was initiated by Beran and Hall. In this paper we introduce and study goodness of fit tests for the coefficient distributions; their asymptotic behaviour under the null hypothesis is obtained. We also propose bootstrap resampling strategies to approach these distributions and prove their asymptotic validity using results by Gine and Zinn on bootstrap empirical processes. A simulation study illustrates the properties of these tests.

Random coefficient regressions: parametric goodness of fit tests

Delicado, Pedro; Romo, Juan
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: Trabalho em Andamento Formato: application/pdf
Publicado em /01/1995 ENG
Relevância na Pesquisa
96.03%
Random coefficient regression models have been applied in different fields during recent years and they are a unifying frame for many statistical models. Recently, Beran and Hall (1992) opened the question of the nonparametric study of the distribution of the coefficients. Nonparametric goodness of fit tests were considered in Delicado and Romo (1994.). In this paper we propose statistics for parametric goodness of fit tests and we obtain their asymptotic distributions. Moreover, we construct bootstrap approximations to these distributions, proving their validity. Finally, a simulation study illustrates our results.

Exact goodness-of-fit tests for censored dats

Grané, Aurea
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: Trabalho em Andamento Formato: text/plain; application/octet-stream; application/octet-stream; application/octet-stream; application/pdf
Publicado em /05/2009 ENG
Relevância na Pesquisa
95.95%
The statistic introduced in Fortiana and Grané (2003) is modified so that it can be used to test the goodness-of-fit of a censored sample, when the distribution function is fully specified. Exact and asymptotic distributions of three modified versions of this statistic are obtained and exact critical values are given for different sample sizes. Empirical power studies show the good performance of these statistics in detecting symmetrical alternatives.

A goodnes-of-fit test based on ranks for arma models

Ferretti, Nélida E.; Kelmansky, Diana M.; Yohai, Víctor J.
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: Trabalho em Andamento Formato: application/pdf
Publicado em /01/1992 ENG
Relevância na Pesquisa
85.88%
In this paper we introduce a goodness-of-fit test based on ranks for ARMA models. The classical portmanteau statistic is generalized to a class of estimators based on ranks. The asymptotic distributions of the proposed statistics are derived. Simulation results suggest that the proposed statistics have good robustness properties for an adequate choice of the score functions.

Bootstrap goodness-of-fit tests for farima models

Delgado, Miguel A.; Hidalgo, Javier
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: Trabalho em Andamento Formato: application/pdf
Publicado em /05/1999 ENG
Relevância na Pesquisa
95.95%
This paper proposes goodness-of-fit tests for the class of covariance stationary FARIMA processes. They are based on functionals of weighted empirical processes, say Sn C.), where the weights are the relative error between the periodogram and the fitted spectral density function under the null specification of the data. Two examples of such functionals are the Tp - Barlett and the Cramer-Von Mises standardized ro - statistics. We show that the tests are able to detect contiguous alternatives converging to the null at the rate n-JI2 • However, because the cumbersome covariance structure of the limiting process of Sn C.), tests based on its asymptotic distribution are difficult to implement in practice_ To circumvent this problem, we propose a bootstrap test, showing its consistency, and studying its small sample performance by a Monte Carlo experiment. __________________________________________________

Goodness of fit tests in random coefficient regression models.

Delicado, Pedro; Romo Urroz, Juan
Fonte: Springer. Publicador: Springer.
Tipo: info:eu-repo/semantics/acceptedVersion; info:eu-repo/semantics/article Formato: application/pdf
Publicado em /03/1999 ENG
Relevância na Pesquisa
95.96%
Random coefficient regressions have been applied in a wide range of fields, from biology to economics, and constitute a common frame for several important statistical models. A nonparametric approach to inference in random coefficient models was initiated by Beran and Hall. In this paper we introduce and study goodness of fit tests for the coefficient distributions; their asymptotic behavior under the null hypothesis is obtained. We also propose bootstrap resampling strategies to approach these distributions and prove their asymptotic validity using results by Giné and Zinn on bootstrap empirical processes. A simulation study illustrates the properties of these tests.

A new goodness-of-fit process for varma (p,q) models: construction and empirical properties

Velilla, Santiago; Nguyen, Huong
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: info:eu-repo/semantics/draft; info:eu-repo/semantics/workingPaper
Publicado em /12/2013 ENG
Relevância na Pesquisa
96.11%
As an extension of the univariate technique in Ubierna and Velilla (2007), we present a goodness-of-fit process for VARMA (p,q) models in which the residuals of the fit are considered. We also formulatean explicit form of the asymptotic covariance function, as well as a suitable representation of the limitprocess. More importantly, we propose a new goodness-of-fit process based on a transformed correlationmatrix sequence. The new goodness-of-fit process is proved to converge weakly to the Brownian bridge.Several simulations, comparisons, and examples are presented. These results illustrate the scope of bothour theoretical findings and contributions. Our method is shown to be sensitive to detect lack of fit.Thus, it can be considered as a useful tool tool for identifying a proper time series model.; Research partially supported by Grant ECO2011-25706 (Spain)

Goodness-of-fit test for randomly censored data based on maximum correlation

Strzalkowska-Kominiak, Ewa; Grané, Aurea
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: info:eu-repo/semantics/draft; info:eu-repo/semantics/workingPaper
Publicado em /07/2014 ENG
Relevância na Pesquisa
95.95%
In this paper we study the goodness-of-fit test introduced by Fortiana and Grané (2003) and Grané (2012), in the context of randomly censored data. We construct a new test statistic undergeneral right-censoring, i.e., with unknown censoring distribution, and prove its asymptoticproperties. Additionally, we study a special case, when the censoring mechanism follows the well-known Koziol-Green model. We present an extensive simulation study on the empirical power of these two versions of the test statistic. We show the good performance of the test statistics in detecting symmetrical alternatives and their advantages over the most famousPearson-type test proposed by Akritas (1988). Finally, we apply our test to the head-and-neck-cancer data; This work has been partially supported by Spanish grants MTM2010-17323 (Spanish Ministry of Science and Innovation), MTM2011-22392, ECO2011-25706 (Spanish Ministry of Economy and Competitiveness)

On the role played by the fixed bandwidth in the Bickel-Rosenblatt goodness-of-fit test

Tenreiro, Carlos
Fonte: Universidade Autônoma de Barcelona Publicador: Universidade Autônoma de Barcelona
Tipo: Artigo de Revista Científica Formato: application/pdf
Publicado em //2005 ENG
Relevância na Pesquisa
95.95%
For the Bickel-Rosenblatt goodness-of-fit test with fixed bandwidth studied by Fan (1998) we derive its Bahadur exact slopes in a neighbourhood of a simple hypothesis f =f0 and we use them to get a better understanding on the role played by the smoothing parameter in the detection of departures from the null hypothesis. When f0 is a univariate normal distribution and we take for kernel the standard normal density function, we compute these slopes for a set of Edgeworth alternatives which give us a description of the test properties in terms of the bandwidth h. A simulation study is presented which indicates that finite sample properties are in good accordance with the theoretical properties based on Bahadur local efficiency. Comparisons with the quadratic classical EDF tests lead us to recommend a test based on a combination of bandwidths in alternative to Anderson-Darling or Cramér-von Mises tests.; Per al contrast de bondat d’ajust de Bickel-Rosenblatt amb amplada de banda fixa, estudiat per Fan (1998), derivem la seva pendent exacta de Bahadur en un entorn d’una hipòtesi simple f = f0 i la utilitzem per obtenir un coneixement millor del paper del paràmetre suavitzador en la detecci´o de desviacions de la hipòtesi nul·la. Quan f0 és una distribució normal univariant i agafem com a nucli la funció de densitat de la normal estàndard...

Quantum chi-squared and goodness of fit testing

Temme, Kristan; Verstraete, Frank
Fonte: American Institute of Physics Publicador: American Institute of Physics
Tipo: Article; PeerReviewed Formato: application/pdf; application/pdf
Publicado em /01/2015
Relevância na Pesquisa
76.03%
A quantum mechanical hypothesis test is presented for the hypothesis that a certain setup produces a given quantum state. Although the classical and the quantum problems are very much related to each other, the quantum problem is much richer due to the additional optimization over the measurement basis. A goodness of fit test for i.i.d quantum states is developed and a max-min characterization for the optimal measurement is introduced. We find the quantum measurement which leads both to the maximal Pitman and Bahadur efficiencies, and determine the associated divergence rates. We discuss the relationship of the quantum goodness of fit test to the problem of estimating multiple parameters from a density matrix. These problems are found to be closely related and we show that the largest error of an optimal strategy, determined by the smallest eigenvalue of the Fisher information matrix, is given by the divergence rate of the goodness of fit test.

Robustness, semiparametric estimation and goodness-of-fit of latent trait models.

Tzamourani, Panagiota
Fonte: London School of Economics and Political Science Thesis Publicador: London School of Economics and Political Science Thesis
Tipo: Thesis; NonPeerReviewed Formato: application/pdf
Publicado em //1999 EN
Relevância na Pesquisa
76.05%
This thesis studies the one-factor latent trait model for binary data. In examines the sensitivity of the model when the assumptions about the model are violated, it investigates the information about the prior distribution when the model is estimated semi-parametrically and it also examines the goodness-of-fit of the model using Monte-Carlo simulations. Latent trait models are applied to data arising from psychometric tests, ability tests or attitude surveys. The data are often contaminated by guessing, cheating, unwillingness to give the true answer or gross errors. To study the sensitivity of the model when the data are contaminated we derive the Influence Function of the parameters and the posterior means, a tool developed in the frame of robust statistics theory. We study the behaviour of the Influence Function for changes in the data and also the behaviour of the parameters and the posterior means when the data are artificially contaminated. We further derive the Influence Function of the parameters and the posterior means for changes in the prior distribution and study empirically the behaviour of the model when the prior is a mixture of distributions. Semiparametric estimation involves estimation of the prior together with the item parameters. A new algorithm for fully semiparametric estimation of the model is given. The bootstrap is then used to study the information on the latent distribution than can be extracted from the data when the model is estimated semiparametrically. The use of the usual goodness-of-fit statistics has been hampered for latent trait models because of the sparseness of the tables. We propose the use of Monte-Carlo simulations to derive the empirical distribution of the goodness-of-fit statistics and also the examination of the residuals as they may pinpoint to the sources of bad fit.

Industrial psychology: Goodness of fit? Fit for goodness?

van Vuuren,Leon J.
Fonte: SA Journal of Industrial Psychology Publicador: SA Journal of Industrial Psychology
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/01/2010 EN
Relevância na Pesquisa
106.16%
ORIENTATION: This theoretical opinion-based paper represents a critical reflection on the relevance of industrial psychology. RESEARCH PURPOSE: Against a historical-developmental background of the discipline, the inquiry questions its goodness of fit, that is its contribution to organisation and society. MOTIVATION FOR THE STUDY: Regular introspection in the discipline ensures that it remains relevant in both science and practice. As such, such introspection calls for a meta-theoretical imperative, to ensure that industrial psychology is fully aware of how the theoretical models applied in the discipline influence people and the society that they form part of RESEARCH DESIGN, APPROACH AND METHOD: The question of industrial Psychology's potential fit for goodness that is broader than what is merely good for the organisation and its employees is explored with a view to enhancing its relevance. The exploration is conducted through the utilisation of theoretical argumentation in which industrial psychology is analysed in terms of contextual considerations that require the discipline to evaluate its real versus its potential contribution to society. MAIN FINDINGS: It is found that the fit is limited to its relevance for inwardly focused organisational behaviour due to its endorsement of the instrumental (strategic) motives of organisations that subscribe to an owner and/or shareholder agenda. PRACTICAL/MANAGERIAL IMPLICATIONS: In light of the main finding...