Density estimate and its application to analysis of temperature
series

J 2003

Density estimate and its application to analysis of temperature series

HOROVÁ, Ivanka, Jiří ZELINKA, Rudolf BRÁZDIL and Marie BUDÍKOVÁ

Basic information

Original name

Density estimate and its application to analysis of temperature series

Authors

HOROVÁ, Ivanka (203 Czech Republic, guarantor), Jiří ZELINKA (203 Czech Republic), Rudolf BRÁZDIL (203 Czech Republic) and Marie BUDÍKOVÁ (203 Czech Republic)

Edition

Environmetrics, Chichester, John Wiley & Sons, 2003, 1180-4009

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10101 Pure mathematics

Country of publisher

United Kingdom of Great Britain and Northern Ireland

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

Odkaz na text článku na internetových stránkách časopisu Environmetrics

Impact factor

Impact factor: 0.598

RIV identification code

RIV/00216224:14310/03:00007953

Organization unit

Faculty of Science

UT WoS

000180856800007

Keywords in English

kernel estimate; visualization; air temperature; Prague-Klementinum; Central England

Abstract

V originále

Nonparametric density estimates attempt to reconstruct the probability density from which a random sample has come, using the sample values and as few assumptions as possible about the density. These methods are smoothing operations on the sample distribution. Methods of kernel estimates represent one of the most effective nonparametric methods. These methods are simple to understand, easy to implement and they have very good mathematical properties. We employed the automatic procedure for the selection of the bandwidth, the kernel and the order of the kernel. This procedure is used for analysis of air temperature fluctuations for series of Central England and Prague-Klementinum in the periods 1661-2000 and 1771-2000, respectively. Graphical representation of the family of estimated densities in three dimensional space provide a better explanation of the long-term trends in temperature distribution of both series.

Links

GA205/01/1067, research and development project

Name: Meteorologické extrémy a jejich dopady v Českých zemích od 16. století

Investor: Czech Science Foundation, Meteorological extremes and their impacts in the Czech Lands since the 16th century

MSM 143100001, plan (intention)

Name: Funkcionální diferenciální rovnice a matematicko-statistické modely

Investor: Ministry of Education, Youth and Sports of the CR, Functional-differential equations and mathematical-statistical models

Citovat

HOROVÁ, Ivanka, Jiří ZELINKA, Rudolf BRÁZDIL and Marie BUDÍKOVÁ. Density estimate and its application to analysis of temperature series. Environmetrics. Chichester: John Wiley & Sons, 2003, vol. 14, No 1, p. 87-102. ISSN 1180-4009.

@article{484458,
   author = {Horová, Ivanka and Zelinka, Jiří and Brázdil, Rudolf and Budíková, Marie},
   article_location = {Chichester},
   article_number = {1},
   keywords = {kernel estimate; visualization; air temperature; Prague-Klementinum; Central England},
   language = {eng},
   issn = {1180-4009},
   journal = {Environmetrics},
   title = {Density estimate and its application to analysis of temperature series},
   url = {http://www3.interscience.wiley.com/cgi-bin/fulltext?ID=102526603&PLACEBO=IE.pdf},
   volume = {14},
   year = {2003}
}

TY  - JOUR
ID  - 484458
AU  - Horová, Ivanka - Zelinka, Jiří - Brázdil, Rudolf - Budíková, Marie
PY  - 2003
TI  - Density estimate and its application to analysis of temperature series
JF  - Environmetrics
VL  - 14
IS  - 1
SP  - 87-102
EP  - 87-102
PB  - John Wiley & Sons
SN  - 11804009
KW  - kernel estimate
KW  - visualization
KW  - air temperature
KW  - Prague-Klementinum
KW  - Central England
UR  - http://www3.interscience.wiley.com/cgi-bin/fulltext?ID=102526603&PLACEBO=IE.pdf
N2  - Nonparametric density estimates attempt to reconstruct the probability density from which a random sample has come, using the sample values and as few assumptions as possible about the density. These methods are smoothing operations on the sample distribution. Methods of kernel estimates represent one of the most effective nonparametric methods. These methods are simple to understand, easy to implement and they have very good mathematical properties. We employed the automatic procedure for the selection of the bandwidth, the kernel and the order of the kernel. This procedure is used for analysis of air temperature fluctuations for series of Central England and Prague-Klementinum in the periods 1661-2000 and 1771-2000, respectively. Graphical representation of the family of estimated densities in three dimensional space provide a better explanation of the long-term trends in temperature distribution of both series.
ER  -

HOROVÁ, Ivanka, Jiří ZELINKA, Rudolf BRÁZDIL and Marie BUDÍKOVÁ. Density estimate and its application to analysis of temperature series. \textit{Environmetrics}. Chichester: John Wiley \&{} Sons, 2003, vol.~14, No~1, p.~87-102. ISSN~1180-4009.

Detailed Information on Publication Record