Recent advances in functional data analysis and high-dimensional statistics
Recent advances in functional data analysis and high-dimensional statistics - ScienceDirect
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Functional data analysis for density functions by transformation to a Hilbert space
A Petersen, HG Müller - 2016 - projecteuclid.org
The Wasserstein metric, Wasserstein–Fréchet mean, simulation results and additional
proofs. The supplementary material includes additional discussion on the Wasserstein …
proofs. The supplementary material includes additional discussion on the Wasserstein …
Modeling probability density functions as data objects
Recent developments in the probabilistic and statistical analysis of probability density
functions are reviewed. Density functions are treated as data objects for which suitable …
functions are reviewed. Density functions are treated as data objects for which suitable …
Computer-aided diagnosis of abnormal breasts in mammogram images by weighted-type fractional Fourier transform
Abnormal breast can be diagnosed using the digital mammography. Traditional manual
interpretation method cannot yield high accuracy. In this study, we proposed a novel …
interpretation method cannot yield high accuracy. In this study, we proposed a novel …
Kernel Partial Correlation Coefficient---a Measure of Conditional Dependence
We propose and study a class of simple, nonparametric, yet interpretable measures of
conditional dependence, which we call kernel partial correlation (KPC) coefficient, between …
conditional dependence, which we call kernel partial correlation (KPC) coefficient, between …
Glucodensities: A new representation of glucose profiles using distributional data analysis
Biosensor data have the potential to improve disease control and detection. However, the
analysis of these data under free-living conditions is not feasible with current statistical …
analysis of these data under free-living conditions is not feasible with current statistical …
Forecasting of density functions with an application to cross-sectional and intraday returns
This paper is concerned with the forecasting of probability density functions. Density
functions are nonnegative and have a constrained integral, and thus do not constitute a …
functions are nonnegative and have a constrained integral, and thus do not constitute a …
Wasserstein autoregressive models for density time series
C Zhang, P Kokoszka… - Journal of Time Series …, 2022 - Wiley Online Library
Data consisting of time‐indexed distributions of cross‐sectional or intraday returns have
been extensively studied in finance, and provide one example in which the data atoms …
been extensively studied in finance, and provide one example in which the data atoms …
40 years after Aitchison's article'The statistical analysis of compositional data': where we are and where we are heading
G Coenders, JJ Egozcue, K Fačevicová… - SORT: statistics and …, 2023 - dugi-doc.udg.edu
The year 2022 marked 40 years since Aitchison published the article'The statistical analysis
of compositional data'. It is considered to be the foundation of contemporary compositional …
of compositional data'. It is considered to be the foundation of contemporary compositional …
Compositional regression with functional response
R Talská, A Menafoglio, J Machalová, K Hron… - … Statistics & Data …, 2018 - Elsevier
The problem of performing functional linear regression when the response variable is
represented as a probability density function (PDF) is addressed. PDFs are interpreted as …
represented as a probability density function (PDF) is addressed. PDFs are interpreted as …