[图书][B] Functional data analysis with R
Emerging technologies generate data sets of increased size and complexity that require
new or updated statistical inferential methods and scalable, reproducible software. These …
new or updated statistical inferential methods and scalable, reproducible software. These …
Fast generalized functional principal components analysis
We propose a new fast generalized functional principal components analysis (fast-GFPCA)
algorithm for dimension reduction of non-Gaussian functional data. The method consists …
algorithm for dimension reduction of non-Gaussian functional data. The method consists …
Model-assisted estimation in high-dimensional settings for survey data
Model-assisted estimators have attracted a lot of attention in the last three decades. These
estimators attempt to make an efficient use of auxiliary information available at the …
estimators attempt to make an efficient use of auxiliary information available at the …
On estimators of the mean of infinite dimensional data in finite populations
A Dey, P Chaudhuri - Bernoulli, 2024 - projecteuclid.org
On estimators of the mean of infinite dimensional data in finite populations Page 1 Bernoulli
30(1), 2024, 797–824 https://doi.org/10.3150/23-BEJ1617 On estimators of the mean of …
30(1), 2024, 797–824 https://doi.org/10.3150/23-BEJ1617 On estimators of the mean of …
Sample-based estimation of mean electricity consumption curves for small domains
A De Moliner, C Goga - Survey Methodology, 2018 - go.gale.com
Many studies conducted by various electric utilities around the world are based on the
analysis of mean electricity consumption curves for various subpopulations, particularly …
analysis of mean electricity consumption curves for various subpopulations, particularly …
Analysing large datasets of functional data: a survey sampling point of view
At the age of Big Data, it is now common to have to deal with very large datasets of
phenomena that evolve over time. When the aim is to estimate simple quantities such as the …
phenomena that evolve over time. When the aim is to estimate simple quantities such as the …
Comments on" Jean-Claude Deville's contributions to survey theory and official statistics": Jean-Claude Deville: Mathematics lover, high-flying researcher, and …
C Goga, A Ruiz-Gazen - Survey Methodology, 2023 - go.gale.com
Jean-Claude Deville is one of the most prominent researcher in survey sampling theory and
practice. His research on balanced sampling, indirect sampling and calibration in particular …
practice. His research on balanced sampling, indirect sampling and calibration in particular …
Large Sample Inference in Finite Population Problems
A Dey - 2024 - library.isical.ac.in
In sample survey, estimation of different finite population parameters like, mean, median,
variance, coefficient of variation, correlation and regression coefficients, interquartile range …
variance, coefficient of variation, correlation and regression coefficients, interquartile range …
Estimation of total electricity consumption curves by sampling in a finite population when some trajectories are partially unobserved
Millions of smart meters that are able to collect individual load curves, that is, electricity
consumption time series, of residential and business customers at fine scale time grids are …
consumption time series, of residential and business customers at fine scale time grids are …
Estimating with kernel smoothers the mean of functional data in a finite population setting. A note on variance estimation in presence of partially observed trajectories
This paper studies, in a survey sampling framework with unequal probability sampling
designs, three nonparametric kernel estimators for the mean curve in presence of …
designs, three nonparametric kernel estimators for the mean curve in presence of …