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CSDA
2006
109views more  CSDA 2006»
13 years 4 months ago
Possibility theory and statistical reasoning
Numerical possibility distributions can encode special convex families of probability measures. The connection between possibility theory and probability theory is potentially fru...
Didier Dubois
CSDA
2006
97views more  CSDA 2006»
13 years 4 months ago
Fuzzy multidimensional scaling
Multidimensional scaling (MDS) is a data analysis technique for representing measurements of (dis)similarity among pairs of objects as distances between points in a low-dimensiona...
Pierre-Alexandre Hébert, Marie-Hél&e...
CSDA
2006
98views more  CSDA 2006»
13 years 4 months ago
Frequency estimation of undamped exponential signals using genetic algorithms
: In this paper, we consider the problem of frequency estimation of undamped superimposed exponential signals model. We propose two iterative techniques of frequency estimation usi...
Amit Mitra, Debasis Kundu, Gunjan Agrawal
CSDA
2006
72views more  CSDA 2006»
13 years 4 months ago
Generalized theory of uncertainty (GTU) - principal concepts and ideas
Uncertainty is an attribute of information. The path-breaking work of Shannon has led to a universal acceptance of the thesis that information is statistical in nature. Concomitan...
Lotfi A. Zadeh
CSDA
2006
96views more  CSDA 2006»
13 years 4 months ago
Analysis of new variable selection methods for discriminant analysis
Several methods to select variables that are subsequently used in discriminant analysis are proposed and analysed. The aim is to find from among a set of m variables a smaller sub...
Joaquín A. Pacheco, Silvia Casado, Laura N&...
CSDA
2006
98views more  CSDA 2006»
13 years 4 months ago
Fast estimation algorithm for likelihood-based analysis of repeated categorical responses
Likelihood-based marginal regression modelling for repeated, or otherwise clustered, categorical responses is computationally demanding. This is because the number of measures nee...
Jukka Jokinen
CSDA
2006
191views more  CSDA 2006»
13 years 4 months ago
Forecasting daily time series using periodic unobserved components time series models
We explore a periodic analysis in the context of unobserved components time series models that decompose time series into components of interest such as trend, seasonal and irregu...
Siem Jan Koopman, Marius Ooms
CSDA
2006
142views more  CSDA 2006»
13 years 4 months ago
Automatic approximation of the marginal likelihood in non-Gaussian hierarchical models
Fitting of non-Gaussian hierarchical random effects models by approximate maximum likelihood can be made automatic to the same extent that Bayesian model fitting can be automated ...
Hans J. Skaug, David A. Fournier