Results 21 to 30 of about 19,219 (292)

Semi- and Nonparametric ARCH Processes

open access: yesJournal of Probability and Statistics, 2011
ARCH/GARCH modelling has been successfully applied in empirical finance for many years. This paper surveys the semiparametric and nonparametric methods in univariate and multivariate ARCH/GARCH models.
Oliver B. Linton, Yang Yan
doaj   +1 more source

Semiparametric Regression in Capture–Recapture Modeling [PDF]

open access: yesBiometrics, 2006
SummaryCapture–recapture models were developed to estimate survival using data arising from marking and monitoring wild animals over time. Variation in survival may be explained by incorporating relevant covariates. We propose nonparametric and semiparametric regression methods for estimating survival in capture–recapture models.
Gimenez, Olivier   +4 more
openaire   +3 more sources

Modeling Environmental Pollution Using Varying-Coefficients Quantile Regression Models under Log-Symmetric Distributions

open access: yesAxioms, 2023
Many phenomena can be described by random variables that follow asymmetrical distributions. In the context of regression, when the response variable Y follows such a distribution, it is preferable to estimate the response variable for predictor values ...
Luis Sánchez   +3 more
doaj   +1 more source

Comparing parametric and semiparametric error correction models for estimation of long run equilibrium between exports and imports

open access: yesApstract: Applied Studies in Agribusiness and Commerce, 2017
This paper introduces the semiparametric error correction model for estimation of export-import relationship as an alternative to the least squares approach.
Henry De-Graft Acquah   +1 more
doaj   +1 more source

Semiparametric modeling of multiple quantiles

open access: yesJournal of Econometrics, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Catania L., Luati A.
openaire   +4 more sources

Semiparametric Regression Analysis via Infer.NET

open access: yesJournal of Statistical Software, 2018
We provide several examples of Bayesian semiparametric regression analysis via the Infer.NET package for approximate deterministic inference in Bayesian models.
Jan Luts   +3 more
doaj   +1 more source

Model and Variable Selection Procedures for Semiparametric Time Series Regression

open access: yesJournal of Probability and Statistics, 2009
Semiparametric regression models are very useful for time series analysis. They facilitate the detection of features resulting from external interventions.
Risa Kato, Takayuki Shiohama
doaj   +1 more source

NONPARAMETRIC ESTIMATION OF SEMIPARAMETRIC TRANSFORMATION MODELS [PDF]

open access: yesEconometric Theory, 2016
In this paper we develop a nonparametric estimation technique for semiparametric transformation models of the form:H(Y) =φ(Z) +X′β+UwhereH,φare unknown functions,βis an unknown finite-dimensional parameter vector and the variables (Y,Z) are endogenous.
Florens, Jean-Pierre, Sokullu, Senay
openaire   +3 more sources

Semi-parametric estimation for ARCH models

open access: yesAlexandria Engineering Journal, 2018
In this paper, we conduct semi-parametric estimation for autoregressive conditional heteroscedasticity (ARCH) model with Quasi likelihood (QL) and Asymptotic Quasi-likelihood (AQL) estimation methods.
Raed Alzghool, Loai M. Al-Zubi
doaj   +1 more source

A semiparametric model for cluster data

open access: yesThe Annals of Statistics, 2009
In the analysis of cluster data, the regression coefficients are frequently assumed to be the same across all clusters. This hampers the ability to study the varying impacts of factors on each cluster. In this paper, a semiparametric model is introduced to account for varying impacts of factors over clusters by using cluster-level covariates.
Zhang, Wenyang, Fan, Jianqing, Sun, Yan
openaire   +4 more sources

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