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Modelling outliers and structural breaks in dynamic linear models with a novel use of a heavy tailed prior for the variances: An alternative to the Inverted Gamma
Modelling outliers structural breaks Inverted Gamma
2011/7/19
In this paper we propose a new wider class of hypergeometric heavy tailed priors that are given as the convolution of a Student-t density for the location parameter and a Scaled Beta2 prior for the va...
Outliers and patterns of outliers in contingency tables with Algebraic Statistics
Algebraic Statistics goodness-of-fi t tests log-linear mod-els toric models
2011/3/18
In this paper we provide a definition of pattern of outliers in contingency tables within a model-based framework. In particular, we make use of log-linear models and exact goodness-of-fit tests to sp...
Outliers in INAR(1) models
integer-valued autoregressivemodels additive and innovational outliers conditionalleast squares estimators strong consistency
2010/3/19
In this paper the integer-valued autoregressive model of order one, contaminated with
additive or innovational outliers is studied in some detail. Moreover, parameter estimation
is also addressed. S...
Identifying outliers in Bayesian hierarchical models: a simulation-based approach
Hierarchical models diagnostics outliers distributional assumptions
2009/9/22
A variety of simulation-based techniques have been proposed for detec-
tion of divergent behaviour at each level of a hierarchical model. We investigate a
diagnostic test based on measuring the coni...
Dynamic factor models have a wide range of applications in econometrics and applied economics. The basic motivation resides in their capability of reducing a large set of time series to only few indic...
Propagation of outliers in multivariate data
Breakdown point contamination model independent contamination influence function robustness
2010/3/18
We investigate the performance of robust estimates of multivariate
location under nonstandard data contamination models such as
componentwise outliers (i.e., contamination in each variable is indepe...
PENALIZED TRIMMED SQUARES AND A MODIFICATION OF SUPPORT VECTORS FOR UNMASKING OUTLIERS IN LINEAR REGRESSION
robust regression mixed integer programming penalty method least trimmed squares identifying outliers support vector machines
2009/2/25
We consider the problem of identifying multiple outliers in linear regression models.
We propose a penalized trimmed squares (PTS) estimator, where penalty costs for discarding outliers are inserted ...
A new graphical tool of outliers detection in regression models based on recursive estimation
outliers graphical tool multiple regression recursive estimation recursive resiudals
2010/4/30
We present in this paper a new tool for outliers detection in the context of multiple regression models. This graphical tool is
based on recursive estimation of the parameters. Simulations were carri...