Results 21 to 30 of about 5,783,966 (296)

Use of Two Smoothing Parameters in Penalized Spline Estimator for Bi-variate Predictor Non-parametric Regression Model [PDF]

open access: yesJournal of Sciences, Islamic Republic of Iran, 2020
Penalized spline criteria involve the function of goodness of fit and penalty, which in the penalty function contains smoothing parameters. It serves to control the smoothness of the curve that works simultaneously with point knots and spline degree. The
Anna Islamiyati
doaj   +1 more source

ercbk/nested-cross-validation-comparison: v1.0

open access: yes, 2021
Experimenting with various implementations and methods of nested cross-validation in R and ...
Eric Book
core   +1 more source

Choice of Smoothing Parameter for Kernel Type Ridge Estimators in Semiparametric Regression Models

open access: yesRevstat Statistical Journal, 2021
This paper concerns kernel-type ridge estimators of parameters in a semiparametric model. These estimators are a generalization of the well-known Speckman’s approach based on kernel smoothing method. The most important factor in achieving this smoothing
Ersin Yilmaz   +2 more
doaj   +1 more source

Asymptotic optimality of generalized C, cross-validation, and generalized cross-validation in regression with heteroskedastic errors [PDF]

open access: yesJournal of Econometrics, 1991
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Spatial Regression Models for Field Trials: A Comparative Study and New Ideas

open access: yesFrontiers in Plant Science, 2022
Naturally occurring variability within a study region harbors valuable information on relationships between biological variables. Yet, spatial patterns within these study areas, e.g., in field trials, violate the assumption of independence of ...
Stijn Hawinkel   +5 more
doaj   +1 more source

A Weighted Generalized Maximum Entropy Estimator with a Data-driven Weight

open access: yesEntropy, 2009
The method of Generalized Maximum Entropy (GME), proposed in Golan, Judge and Miller (1996), is an information-theoretic approach that is robust to multicolinearity problem.
Ximing Wu
doaj   +1 more source

Explaining the Generalized Cross-Validation on Linear Models [PDF]

open access: yesJournal of Mathematics and Statistics, 2019
Cross-Validation is a model validation method widely used by the scientific community. The Generalized Cross-Validation (GCV) is an invariant version of the usual Cross-Validation method. This generalization was obtained using the non usual theory of circulant complex matrices.
Chaves, Lucas Monteiro   +3 more
openaire   +1 more source

A Quantitative Comparison of Overlapping and Non-Overlapping Sliding Windows for Human Activity Recognition Using Inertial Sensors

open access: yesSensors, 2019
The sliding window technique is widely used to segment inertial sensor signals, i.e., accelerometers and gyroscopes, for activity recognition. In this technique, the sensor signals are partitioned into fix sized time windows which can be of two types: (1)
Akbar Dehghani   +3 more
doaj   +1 more source

KNOT OPTIMIZATION FOR BI-RESPONSE SPLINE NONPARAMETRIC REGRESSION WITH GENERALIZED CROSS-VALIDATION (GCV)

open access: yesBarekeng
Nonparametric regression is a statistical method used to model relationships between variables without making strong assumptions about the functional form of the relationship.
Andre Fajry Al Barra   +1 more
doaj   +1 more source

Geographically weighted generalized poisson regression model with the best kernel function in the case of the number of postpartum maternal mortality in east java

open access: yesMethodsX, 2023
This study proposes a Geographically Weighted Generalized Poisson Regression (GWGPR) model with the best kernel function to obtain a model of the number of postpartum maternal mortality in East Java Province in 2020 and determine the factors that affect ...
Sischa Wahyuning Tyas   +2 more
doaj   +1 more source

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