Highly Robust Estimation of the Autocorrelation Coefficient
Kalina, Jan; Vlčková, Katarína
2014 - English
The classical autocorrelation coefficient estimator in the time series context is very sensitive to the presence of outlying measurements in the data. This paper proposes several new robust estimators of the autocorrelation coefficient. First, we consider an autoregressive process of the first order AR(1) to be observed. Robust estimators of the autocorrelation coefficient are proposed in a straightforward way based on robust regression. Further, we consider the task of robust estimation of the autocorrelation coefficient of residuals of linear regression. The task is connected to verifying the assumption of independence of residuals and robust estimators of the autocorrelation coefficient are defined based on the Durbin-Watson test statistic for robust regression. The main result is obtained for the implicitly weighted autocorrelation coefficient with small weights assigned to outlying measurements. This estimator is based on the least weighted squares regression and we exploit its asymptotic properties to derive an asymptotic test that the autocorrelation coefficient is equal to 0. Finally, we illustrate different estimators on real economic data, which reveal the advantage of the approach based on the least weighted squares regression. The estimator turns out to be resistant against the presence of outlying measurements.
Keywords:
time series; autoregressive process; linear regression; robust econometrics
Available on request at various institutes of the ASCR
Highly Robust Estimation of the Autocorrelation Coefficient
The classical autocorrelation coefficient estimator in the time series context is very sensitive to the presence of outlying measurements in the data. This paper proposes several new robust estimators ...
A Weather Risk Prediction System for Road Trip Planning
Krč, Pavel; Fuglík, Viktor; Juruš, Pavel; Kasanický, Ivan; Konár, Ondřej; Pelikán, Emil; Eben, Kryštof; Šucha, M.
2014 - English
The paper presents first ideas of the MEDARD-RODOS project. The aim of the project is to develop a decision support system for road trip planning, reflecting the weather risks predicted from the NWP models implemented in the MEDARD system (www.medard-online.cz) and using the traffic information from the RODOS project (www.centrum-rodos.cz).
Keywords:
weather; prediction; risk; system; road; planning; MEDARD; RODOS; NWP
Available on request at various institutes of the ASCR
A Weather Risk Prediction System for Road Trip Planning
The paper presents first ideas of the MEDARD-RODOS project. The aim of the project is to develop a decision support system for road trip planning, reflecting the weather risks predicted from the NWP ...
Eulerovské chemické transportní modely, jejich výhody a možnosti využití
Resler, Jaroslav; Karel, J.; Jireš, R.; Liczki, Jitka; Belda, Michal; Eben, Kryštof; Kasanický, Ivan; Juruš, Pavel; Vlček, O.; Benešová, N.; Kazmuková, M.
2014 - Czech
Available on request at various institutes of the ASCR
Eulerovské chemické transportní modely, jejich výhody a možnosti využití
Robust Regularized Cluster Analysis for High-Dimensional Data
Kalina, Jan; Vlčková, Katarína
2014 - English
This paper presents new approaches to the hierarchical agglomerative cluster analysis for high-dimensional data. First, we propose a regularized version of the hierarchical cluster analysis for categorical data with a large number of categories. It exploits a regularized version of various test statistics of homogeneity in contingency tables as the measure of distance between two clusters. Further, our aim is cluster analysis of continuous data with a large number of variables. Various regularization techniques tailor-made for high-dimensional data have been proposed, which have however turned out to suffer from a high sensitivity to the presence of outlying measurements in the data. As a robust solution, we recommend to combine two newly proposed methods, namely a regularized version of robust principal component analysis and a regularized Mahalanobis distance, which is based on an asymptotically optimal regularization of the covariance matrix. We bring arguments in favor of the newly proposed methods.
Keywords:
cluster analysis; robust data mining; big data; regularization
Available at various institutes of the ASCR
Robust Regularized Cluster Analysis for High-Dimensional Data
This paper presents new approaches to the hierarchical agglomerative cluster analysis for high-dimensional data. First, we propose a regularized version of the hierarchical cluster analysis for ...
On the Consistency of an Estimator for Hierarchical Archimedean Copulas
Górecki, J.; Hofert, M.; Holeňa, Martin
2014 - English
The paper addresses an estimation procedure for hierarchical Archimedean copulas, which has been proposed in the literature. It is shown here that this estimation is not consistent in general. Furthermore, a correction is proposed, which leads to a consistent estimator.
Keywords:
hierarchical Archimedean copula; Kendall distribution function; parameter estimation; structure determination; consistency
Available on request at various institutes of the ASCR
On the Consistency of an Estimator for Hierarchical Archimedean Copulas
The paper addresses an estimation procedure for hierarchical Archimedean copulas, which has been proposed in the literature. It is shown here that this estimation is not consistent in general. ...
Klasické a současné postupy ve shlukové analýze
Řezanková, Hana
2013 - Czech
Článek se zaměřuje na vývoj vybraných postupů ve shlukové analýze. Jde o nedávno navržené míry podobnosti pro objekty charakterizované nominálními proměnnými, vývoj algoritmů pro k-shlukování a vývoj metod pro shlukování v případě velkých datových souborů a kategoriálních dat. U algoritmů pro k-shlukování je pozornost věnována zohlednění neurčitosti při zařazování objektů do shluků, konkrétně algoritmům FCM (fuzzy k-průměrů), PCM, FPCM, RCM, RFCM a RFPCM. Pro velké datové soubory jsou zařazeny algoritmy CURE, ROCK, CLARA, CLARANS a BIRCH, pro shlukování kategoriálních dat pak algoritmy COOLCAT a ROCK. Zmíněna je též dvoukroková shluková analýza pro shlukování velkých datových souborů s proměnnými různých typů. The paper focuses on the development of selected approaches in cluster analysis. There are recently proposed similarity measures for objects characterized by nominal variables, development of algorithms for k-clustering and development of methods for clustering large data files and categorical data. As concerns algorithms for k-clustering, attention is paid to take into account the uncertainty in classifying objects into clusters, namely FCM (fuzzy k-means), PCM, FPCM, RCM, RFCM and RFPCM algorithms. For large data files, algorithms CURE, ROCK, CLARA, CLARANS and BIRCH are included, for categorical data clustering there are COOLCAT and ROCK algorithms. Two-step cluster analysis to cluster large data sets with variables of different types is mentioned.
Keywords:
shluková analýza; míry podobnosti; nominální proměnné; metody k-průměrů; metody k-medoidů; fuzzy shlukování; velké datové soubory
Available at various institutes of the ASCR
Klasické a současné postupy ve shlukové analýze
Článek se zaměřuje na vývoj vybraných postupů ve shlukové analýze. Jde o nedávno navržené míry podobnosti pro objekty charakterizované nominálními proměnnými, vývoj algoritmů pro k-shlukování a vývoj ...
Brána vědění otevřena: nový pohled na výpočty
Wiedermann, Jiří
2013 - Czech
V práci je představen nový pohled na výpočty - totiž jako na procesy generující znalosti. Tento přístup má široké konotace v oblasti umělé inteligence, v kognitivních vědách, ve filozofii, epistemologii a metodologii vědy. We present a new view of computations - viz. the knowledge generating processes. This approach has many connotations in the area of artificial intelligence, in cognitive sciences, in philosophy, epistemology and methodology of science.
Keywords:
výpočty; procesy; znalost; epistemologie
Available at various institutes of the ASCR
Brána vědění otevřena: nový pohled na výpočty
V práci je představen nový pohled na výpočty - totiž jako na procesy generující znalosti. Tento přístup má široké konotace v oblasti umělé inteligence, v kognitivních vědách, ve filozofii, ...
Posouzení energetické bilance fotovoltaického systému na základě meteorologických dat
Prokop, L.; Mišák, S.; Pelikán, Emil; Juruš, Pavel; Kasanický, Ivan
2013 - Czech
V příspěvku je analyzován koncept energetické bilance pro domácnosti využívající fotovoltaické zdroje energie. Výsledky analýzy spotřeby energie pro vybranou domácnost pak byly využity jako vstup pro posouzení energetické bilance a porovnány s potenciální výrobou energie na základě meteorologických a klimatických dat získaných ze satelitních měření. Byly diskutovány různé možnosti dosažení dostatečného množství dostupné fotovoltaické energie. Energy concept for family house power supply using photovoltaic power plant (PV) with possibility to operate in off-grid mode was analyzed in this paper. We present partial results from analysis of power consumption of selected house. These results were used as input data for energy concept evaluation and compared with potential energy production calculated from meteorological and climatological data gained from meteorological satellite data. Various possibilities to reach sufficient amount of available energy from PV system were discussed in this paper too.
Keywords:
photovoltaic power plant; energy concept; energy consumption; PAX system; solar radiation
Available on request at various institutes of the ASCR
Posouzení energetické bilance fotovoltaického systému na základě meteorologických dat
V příspěvku je analyzován koncept energetické bilance pro domácnosti využívající fotovoltaické zdroje energie. Výsledky analýzy spotřeby energie pro vybranou domácnost pak byly využity jako vstup pro ...
In-Hospital Death Prediction in Patients with Acute Coronary Syndrome
Monhart, Z.; Reissigová, Jindra; Zvárová, Jana; Grünfeldová, H.; Janský, P.; Vojáček, J.; Widimský, P.
2013 - English
Keywords:
acute coronary syndrome; in-hospital death; prediction; multilevel logistic regression; non-PCI hospital
Available at various institutes of the ASCR
In-Hospital Death Prediction in Patients with Acute Coronary Syndrome
Objectification of a Choice of a Spa Treatment Plan for Arthritis of the Hip Joint
Och, F.; Medonos, J.; Hanzlíček, P.; Valenta, Zdeněk; Dvořák, V.; Zvárová, Jana
2013 - English
Keywords:
decision-support; spa treatment; hip arthritis; statistical analysis
Available at various institutes of the ASCR
Objectification of a Choice of a Spa Treatment Plan for Arthritis of the Hip Joint
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