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Wyświetlanie 1-15 z 36
Tytuł:
An Extension of the Classical Distance Correlation Coefficient for Multivariate Functional Data with Applications
Autorzy:
Górecki, Tomasz
Krzyśko, Mirosław
Ratajczak, Waldemar
Wołyński, Waldemar
Powiązania:
https://bibliotekanauki.pl/articles/465741.pdf
Data publikacji:
2016
Wydawca:
Główny Urząd Statystyczny
Tematy:
multivariate functional data
functional data analysis
correlation analysis
Opis:
The relationship between two sets of real variables defined for the same individuals can be evaluated by a few different correlation coefficients. For the functional data we have one important tool: canonical correlations. It is not immediately straightforward to extend other similar measures to the context of functional data analysis. In this work we show how to use the distance correlation coefficient for a multivariate functional case. The approaches discussed are illustrated with an application to some socio-economic data.
Źródło:
Statistics in Transition new series; 2016, 17, 3; 449-466
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Classification problems based on regression models for multi-dimensional functional data
Autorzy:
Górecki, Tomasz
Krzyśko, Mirosław
Wołyński, Waldemar
Powiązania:
https://bibliotekanauki.pl/articles/465780.pdf
Data publikacji:
2015
Wydawca:
Główny Urząd Statystyczny
Tematy:
multivariate functional data
functional data analysis
multivariate functional regression
classification
Opis:
Data in the form of a continuous vector function on a given interval are referred to as multivariate functional data. These data are treated as realizations of multivariate random processes. We use multivariate functional regression techniques for the classification of multivariate functional data. The approaches discussed are illustrated with an application to two real data sets.
Źródło:
Statistics in Transition new series; 2015, 16, 1; 97-110
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Functional Regression in Short-Term Prediction of Economic Time Series
Autorzy:
Kosiorowski, Daniel
Powiązania:
https://bibliotekanauki.pl/articles/465836.pdf
Data publikacji:
2014
Wydawca:
Główny Urząd Statystyczny
Tematy:
functional data analysis
functional time series
prediction
Opis:
We compare four methods of forecasting functional time series including fully functional regression, functional autoregression FAR(1) model, Hyndman & Shang principal component scores forecasting using one-dimensional time series method, and moving functional median. Our comparison methods involve simulation studies as well as analysis of empirical dataset concerning the Internet users behaviours for two Internet services in 2013. Our studies reveal that Hyndman & Shao predicting method outperforms other methods in the case of stationary functional time series without outliers, and the moving functional median induced by Frainman & Muniz depth for functional data outperforms other methods in the case of smooth departures from stationarity of the time series as well as in the case of functional time series containing outliers.
Źródło:
Statistics in Transition new series; 2014, 15, 4; 611-626
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Learning novelty detection outside a class of random curves with application to COVID-19 growth
Autorzy:
Rafajłowicz, Wojciech
Powiązania:
https://bibliotekanauki.pl/articles/2031122.pdf
Data publikacji:
2021
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
classification
learning
novelty detection
functional data
Opis:
Let a class of proper curves is specified by positive examples only. We aim to propose a learning novelty detection algorithm that decides whether a new curve is outside this class or not. In opposite to the majority of the literature, two sources of a curve variability are present, namely, the one inherent to curves from the proper class and observations errors’. Therefore, firstly a decision function is trained on historical data, and then, descriptors of each curve to be classified are learned from noisy observations.When the intrinsic variability is Gaussian, a decision threshold can be established from T2 Hotelling distribution and tuned to more general cases. Expansion coefficients in a selected orthogonal series are taken as descriptors and an algorithm for their learning is proposed that follows nonparametric curve fitting approaches. Its fast version is derived for descriptors that are based on the cosine series. Additionally, the asymptotic normality of learned descriptors and the bound for the probability of their large deviations are proved. The influence of this bound on the decision threshold is also discussed.The proposed approach covers curves described as functional data projected onto a finite-dimensional subspace of a Hilbert space as well a shape sensitive description of curves, known as square-root velocity (SRV). It was tested both on synthetic data and on real-life observations of the COVID-19 growth curves.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2021, 11, 3; 195-215
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Use of functional cluster analysis of CPTU data for assessment of a subsoil rigidity
Autorzy:
Młynarek, Z.
Wierzbicki, J.
Wołyński, W.
Powiązania:
https://bibliotekanauki.pl/articles/178174.pdf
Data publikacji:
2018
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
CPTU
cluster analysis
functional data
rigidity model
Opis:
This paper shows an example of the grouping of piezocone penetration test (CPTU) characteristics using functional data analysis, together with the results of clustering, in the form of a subsoil rigidity model. The subsoil rigidity model was constructed based on layer separation using the proposed method, as well as the k-means method. In the construction of the subsoil rigidity model, the constrained modulus M was applied. These moduli were determined from empirical relationships for overconsolidated and normally consolidated soils from Poland based on cone tip resistance.
Źródło:
Studia Geotechnica et Mechanica; 2018, 40, 2; 117-124
0137-6365
2083-831X
Pojawia się w:
Studia Geotechnica et Mechanica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Ocena zróżnicowania poziomu życia mieszkańców województw w latach 2003–2013 za pomocą składowych głównych dla wielowymiarowych danych funkcjonalnych oraz analizy skupień
Estimation of Diversity of Living Standards in Polish Voivodships in 2003–2013 Using Principal Components for Multidimensional Functional Data and Cluster Analysis
Autorzy:
Krzyśko, Mirosław
Majka, Agnieszka
Wołyński, Waldemar
Powiązania:
https://bibliotekanauki.pl/articles/1050488.pdf
Data publikacji:
2016-03-31
Wydawca:
Główny Urząd Statystyczny
Tematy:
wielowymiarowe dane funkcjonalne
funkcjonalna analiza danych
analiza składowych głównych
multivariate functional data
functional data analysis
principal components analysis
Opis:
W artykule przedstawiono ocenę zróżnicowania poziomu życia mieszkańców województw w latach 2003–2013. Do oceny zastosowano analizę składowych głównych dla wielowymiarowych danych funkcjonalnych oraz dendrytową analizę skupień. Metody te pozwoliły na wyodrębnienie względnie jednorodnych grup województw o zbliżonym poziomie rozpatrywanych cech dla całego rozpatrywanego okresu łącznie.
The paper presents an estimation of life standard diversity for residents of Polish voivodships in 2003–2013. The principal component analysis was applied for multidimensional functional data and the dendrite method was used for cluster analysis. These methods made it possible to isolate relatively homogeneous groups of voivodships that had similar values of characteristics under consideration, for the whole period at issue.
Źródło:
Przegląd Statystyczny; 2016, 63, 1; 81-98
0033-2372
Pojawia się w:
Przegląd Statystyczny
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Functional principal components analysis on the example of the achievements of students in the years 2009-2017
Autorzy:
Sztemberg-Lewandowska, Mirosława
Powiązania:
https://bibliotekanauki.pl/articles/425289.pdf
Data publikacji:
2019
Wydawca:
Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Tematy:
level of students' knowledge
functional data
longitudinal data
functional principal components analysis
Opis:
The functional principal components analysis joins the advantages of the principal components analysis and provide analysis of dynamic data. The main difference in both methods is the type of data the PCA is based on multivariate data, whereas the FPCA on the functional data including curves and trajectories, i.e. a series of individual observations, not a single observation, as usual. The functional principal components analysis with functional data, will be used in the analysis. This method allows the analysis of dynamic data. The purpose of the article is to apply of functional principal components analysis to the problem of student’s achievements. The article was compared the level of students' knowledge during different stages of education in 2009-2017. The analysis covers the average exam results after the II, III and IV stage of education.
Źródło:
Econometrics. Ekonometria. Advances in Applied Data Analytics; 2019, 23, 4; 16-29
1507-3866
Pojawia się w:
Econometrics. Ekonometria. Advances in Applied Data Analytics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Variable selection in multivariate functional data classification
Autorzy:
Górecki, Tomasz
Krzyśko, Mirosław
Wołyński, Waldemar
Powiązania:
https://bibliotekanauki.pl/articles/1194458.pdf
Data publikacji:
2019-07-02
Wydawca:
Główny Urząd Statystyczny
Tematy:
multivariate functional data
variable selection
dCov
HSIC
classification
Opis:
A new variable selection method is considered in the setting of classification with multivariate functional data (Ramsay and Silverman (2005)). The variable selection is a dimensionality reduction method which leads to replace the whole vector process, with a low-dimensional vector still giving a comparable classification error. Various classifiers appropriate for functional data are used. The proposed variable selection method is based on functional distance covariance (dCov) given by Székely and Rizzo (2009, 2012) and the Hilbert-Schmidt Independent Criterion (HSIC) given by Gretton et al. (2005). This method is a modification of the procedure given by Kong et al. (2015). The proposed methodology is illustrated with a real data example.
Źródło:
Statistics in Transition new series; 2019, 20, 2; 123-138
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Statistical risk quantification of two-directional internet traffic flows
Autorzy:
Kokoszka, Piotr
Lin, Mengting
Wang, Haonan
Hayne, Stephen
Powiązania:
https://bibliotekanauki.pl/articles/32222709.pdf
Data publikacji:
2024-03-24
Wydawca:
Główny Urząd Statystyczny
Tematy:
Copula
Functional data
Internet traffic
Principal components
Risk quantification
Opis:
We develop statistical methodology for the quantification of risk of source-destination pairs in an internet network. The methodology is developed within the framework of functional data analysis and copula modeling. It is summarized in the form of computational algorithms that use bidirectional source-destination packet counts as input. The usefulness of our approach is evaluated by an application to real internet traffic flows and via a simulation study.
Źródło:
Statistics in Transition new series; 2024, 25, 1; 1-22
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Outlier detection based on the functional coefficient of variation
Autorzy:
Deveci Kocakoç, Ipek
Köymen Keser, Istem
Powiązania:
https://bibliotekanauki.pl/articles/12289238.pdf
Data publikacji:
2023-03-15
Wydawca:
Główny Urząd Statystyczny
Tematy:
coefficient of variation function
outlier detection
functional data analysis
Opis:
The coefficient of the variation function is a useful descriptive statistic, especially when comparing the variability of more than two curve groups, even when they have significantly different mean curves. Since the coefficient of variation function is the ratio of the mean and standard deviation functions, its particular property is that it shows the acceleration more explicitly than the standard deviation function. The aim of the study is twofold: to show that the functional coefficient of variation is more sensitive to abrupt changes than the functional standard deviation and to propose the utilisation of the functional coefficient of variation as an outlier detection tool. Several simulation trials have shown that the coefficient of the variation function allows the effects of outliers to be seen explicitly.
Źródło:
Statistics in Transition new series; 2023, 24, 2; 1-16
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
On the nonparametric estimation of the conditional hazard estimator in a single functional index
Autorzy:
Gagui, Abdelmalek
Chouaf, Abdelhak
Powiązania:
https://bibliotekanauki.pl/articles/2107053.pdf
Data publikacji:
2022-06-14
Wydawca:
Główny Urząd Statystyczny
Tematy:
single functional index
conditional hazard function
nonparametric estimation
α-mixing dependency
asymptotic normality
functional data
Opis:
This paper deals with the conditional hazard estimator of a real response where the variable is given a functional random variable (i.e it takes values in an infinite-dimensional space). Specifically, we focus on the functional index model. This approach offers a good compromise between nonparametric and parametric models. The principle aim is to prove the asymptotic normality of the proposed estimator under general conditions and in cases where the variables satisfy the strong mixing dependency. This was achieved by means of the kernel estimator method, based on a single-index structure. Finally, a simulation of our methodology shows that it is efficient for large sample sizes.
Źródło:
Statistics in Transition new series; 2022, 23, 2; 89-105
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Information Flows Around the Globe: Predicting Opening Gaps from Overnight Foreign Stock Price Patterns
Autorzy:
De Gooijer, Jan G.
Diks, Cees G. H.
Gątarek, Łukasz T.
Powiązania:
https://bibliotekanauki.pl/articles/483377.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Close-to-open gap forecasting
functional data analysis
international stock markets
nonparametric modeling
Opis:
This paper describes a forecasting exercise of close-to-open returns on major global stock indices, based on high-frequency price patterns that have become available in foreign markets overnight. Generally speaking, out-ofsample forecast performance depends on the forecast method as well as the information that the forecasts are based on. In this paper both aspects are considered. The fact that the close-to-open gap is a scalar response variable to a functional variable, namely an overnight foreign price pattern, brings the prediction exercise in the realm of functional data analysis. Both parametric and non-parametric functional data analysis are considered, and compared with a simple linear benchmark model. The information set is varied by dividing global markets into three clusters, Asia-Pacific, Europe and North-America, and including or excluding price patterns on a per-cluster basis. The overall best performing forecast is nonparametric using all available information, suggesting the presence of nonlinear relations between the overnight price patterns and the opening gaps.
Źródło:
Central European Journal of Economic Modelling and Econometrics; 2012, 4, 1; 23-44
2080-0886
2080-119X
Pojawia się w:
Central European Journal of Economic Modelling and Econometrics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Measuring and Testing Mutual Dependence of Multivariate Functional Data
Autorzy:
Krzyśko, Mirosław
Smaga, Łukasz
Powiązania:
https://bibliotekanauki.pl/articles/1058987.pdf
Data publikacji:
2020-09-04
Wydawca:
Główny Urząd Statystyczny
Tematy:
characteristic function
dependence measure
distance covariance
multivariate functional data
permutation method
test of independence
Opis:
This paper considers new measures of mutual dependence between multiple multivariate random processes representing multidimensional functional data. In the case of two processes, the extension of functional distance correlation is used by selecting appropriate weight function in the weighted distance between characteristic functions of joint and marginal distributions. For multiple random processes, two measures are sums of squared measures for pairwise dependence. The dependence measures are zero if and only if the random processes are mutually independent. This property is used to construct permutation tests for mutual independence of random processes. The finite sample properties of these tests are investigated in simulation studies. The use of the tests and the results of simulation studies are illustrated with an example based on real data.
Źródło:
Statistics in Transition new series; 2020, 21, 3; 21-37
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Some asymptotic results of the estimators for conditional mode for functional data in the single index model missing data at random
Autorzy:
Mekkaoui, Souad
Kadiri, Nadia
Rabhi, Abbes
Powiązania:
https://bibliotekanauki.pl/articles/31340028.pdf
Data publikacji:
2023-11-30
Wydawca:
Główny Urząd Statystyczny
Tematy:
functional data analysis
functional single-index process
kernel estimator
missing at random
non-parametric estimation
small ball probability
Opis:
In this work, we consider the problem of non-parametric estimation of a regression function, namely the conditional density and the conditional mode in a single functional index model (SFIM) with randomly missing data. The main result of this work is the establishment of the asymptotic properties of the estimator, such as almost complete convergence rates. Moreover, the asymptotic normality of the constructs is obtained under certain mild conditions. We finally discuss how to apply our result to construct confidence intervals.
Źródło:
Przegląd Statystyczny; 2023, 70, 2; 20-45
0033-2372
Pojawia się w:
Przegląd Statystyczny
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Forecasting of a Hierarchical Functional Time Series on Example of Macromodel for the Day and Night Air Pollution in Silesia Region — A Critical Overview
Autorzy:
Kosiorowski, Daniel
Mielczarek, Dominik
Rydlewski, Jerzy P.
Powiązania:
https://bibliotekanauki.pl/articles/2076274.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
day and night air pollution
functional data analysis
functionalmedian
hierarchical time series
reconciliation of forecasts
Opis:
In economics we often face a system which intrinsically imposes a structure of hierarchy of its components, i.e., in modeling trade accounts related to foreign exchange or in optimization of regional air protection policy. A problem of reconciliation of forecasts obtained on different levels of hierarchy has been addressed in the statistical and econometric literature many times and concerns bringing together forecasts obtained independently at different levels of hierarchy. This paper deals with this issue with regard to a hierarchical functional time series. We present and critically discuss a state of art and indicate opportunities of an application of these methods to a certain environment protection problem. We critically compare the best predictor known from the literature with our own original proposal. Within the paper we study a macromodel describing the day and night air pollution in Silesia region divided into five subregions.
Źródło:
Central European Journal of Economic Modelling and Econometrics; 2018, 1; 53-73
2080-0886
2080-119X
Pojawia się w:
Central European Journal of Economic Modelling and Econometrics
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 36

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