Fehlerquadratsummen-Minimierung

English translation: minimization of the sum of the squared errors

GLOSSARY ENTRY (DERIVED FROM QUESTION BELOW)
German term or phrase:Fehlerquadratsummen-Minimierung
English translation:minimization of the sum of the squared errors
Entered by: Kim Metzger

18:24 Mar 25, 2009
German to English translations [PRO]
Science - Mathematics & Statistics / multiple linear regression
German term or phrase: Fehlerquadratsummen-Minimierung
Here's the context sentence:
MLR (Multiple Linear Regression) ist eine statische Standardmethode, die basierend auf einer Fehlerquadratsummen-Minimierung eine multiple lineare Regression durchführt.
Holly Hart
United States
Local time: 08:39
minimization of sum of squared error
Explanation:
This isn't my field, but I think this might be in the right direction.

mittleres Fehlerquadrat – mean error square value

http://books.google.com/books?id=NbwrzoLn6cUC&pg=PA509&lpg=P...

Thus, for the impossible ideal of perfect uniformity, where all probe signals are equal and no random error exists, the sum of square value of Error would be zero.

http://www.patentstorm.us/patents/7248973/description.html

sum of squared error

The mean minimizes the sum of squared error. The figure on the left, represents the data in the frequency distribution on the right, and can be used to illustrate this property of the mean.
http://espse.educ.psu.edu/edpsych/faculty/rhale/Statistics/C...

Minimization of sum of squared error in IFT scheme. Fig. 4. Minimization of cost function (sum of squared error) in simulation over 10 cycles of tuning ...
ieeexplore.ieee.org/iel5/4498401/4516026/04516072.pdf?arnumber=4516072
by H Stearns



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Note added at 1 hr (2009-03-25 19:29:23 GMT)
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Sum of squares error gets 32,000 hits vs. 4,600 for sum of squared error

Introduction to Engineering Statistics and Six Sigma: Statistical ... - Google Books Resultby Theodore T. Allen - 2006 - Technology & Engineering - 529 pages
These runs are set aside and not used for estimating the weights in the minimization of the sum of squares error. In the context of welding parameter ...
books.google.com/books?isbn=1852339551...

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Note added at 1 hr (2009-03-25 19:42:11 GMT)
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Abstract The combinatorial problem of clusterwise discrete linear approximation is defined as finding a given number of clusters of observations such that the overall sum of error sum of squares within those clusters becomes a minimum. The FORTRAN implementation of a heuristic solution method and a numerical example are given.

Zusammenfassung Die kombinatorische Aufgabe der klassenweisen diskreten linearen Approximation wird dadurch definiert, daß die Summe über die Fehlerquadratsummen innerhalb der Klassen minimiert wird. Die FORTRAN-Implementation eines heuristischen Lösungsverfahrens und ein numerisches Beispiel werden angegeben.

http://www.springerlink.com/content/62mm101364012334/

ISI glossary of statistical terms – English-German

error sum of squares - Summe der Fehlerquadrate

http://ec.europa.eu/comm/eurostat/research/index.htm?http://...
Selected response from:

Kim Metzger
Mexico
Local time: 07:39
Grading comment
Thanks - especially for all the good references - it was important to include 'sum' here. Thanks to all contributors!
4 KudoZ points were awarded for this answer



Summary of answers provided
4 +1least squares minimisation / least squares method
Michael Watson
4mean-square error minimization
Irina Ion
3 +1minimization of sum of squared error
Kim Metzger
3maximum mean squared error minimization
Lirka


  

Answers


14 mins   confidence: Answerer confidence 3/5Answerer confidence 3/5
maximum mean squared error minimization


Explanation:
I think that's it

Lirka
Austria
Local time: 14:39
Native speaker of: Native in EnglishEnglish
PRO pts in category: 4
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27 mins   confidence: Answerer confidence 4/5Answerer confidence 4/5
mean-square error minimization


Explanation:
The
regression analysis is focused on estimating the regression coefficients, making
statistical inference about these estimations, and constructing forecasts for the
new values of Y, given the new value of X. The estimation is done using the
mean-square error minimization;
http://wolfweb.unr.edu/homepage/zal/STAT452/Lab5.pdf

Irina Ion
Norway
Local time: 14:39
Works in field
Native speaker of: Native in RomanianRomanian

Peer comments on this answer (and responses from the answerer)
agree  Alvaro Ferreira
1 hr

disagree  Oliver Walter: Linear regression minimizes the mean square error but the text mentions minimising the sum: the sum is not the mean. Depending on the rest of the text this difference might be significant.
4 hrs
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50 mins   confidence: Answerer confidence 3/5Answerer confidence 3/5 peer agreement (net): +1
minimization of sum of squared error


Explanation:
This isn't my field, but I think this might be in the right direction.

mittleres Fehlerquadrat – mean error square value

http://books.google.com/books?id=NbwrzoLn6cUC&pg=PA509&lpg=P...

Thus, for the impossible ideal of perfect uniformity, where all probe signals are equal and no random error exists, the sum of square value of Error would be zero.

http://www.patentstorm.us/patents/7248973/description.html

sum of squared error

The mean minimizes the sum of squared error. The figure on the left, represents the data in the frequency distribution on the right, and can be used to illustrate this property of the mean.
http://espse.educ.psu.edu/edpsych/faculty/rhale/Statistics/C...

Minimization of sum of squared error in IFT scheme. Fig. 4. Minimization of cost function (sum of squared error) in simulation over 10 cycles of tuning ...
ieeexplore.ieee.org/iel5/4498401/4516026/04516072.pdf?arnumber=4516072
by H Stearns



--------------------------------------------------
Note added at 1 hr (2009-03-25 19:29:23 GMT)
--------------------------------------------------

Sum of squares error gets 32,000 hits vs. 4,600 for sum of squared error

Introduction to Engineering Statistics and Six Sigma: Statistical ... - Google Books Resultby Theodore T. Allen - 2006 - Technology & Engineering - 529 pages
These runs are set aside and not used for estimating the weights in the minimization of the sum of squares error. In the context of welding parameter ...
books.google.com/books?isbn=1852339551...

--------------------------------------------------
Note added at 1 hr (2009-03-25 19:42:11 GMT)
--------------------------------------------------

Abstract The combinatorial problem of clusterwise discrete linear approximation is defined as finding a given number of clusters of observations such that the overall sum of error sum of squares within those clusters becomes a minimum. The FORTRAN implementation of a heuristic solution method and a numerical example are given.

Zusammenfassung Die kombinatorische Aufgabe der klassenweisen diskreten linearen Approximation wird dadurch definiert, daß die Summe über die Fehlerquadratsummen innerhalb der Klassen minimiert wird. Die FORTRAN-Implementation eines heuristischen Lösungsverfahrens und ein numerisches Beispiel werden angegeben.

http://www.springerlink.com/content/62mm101364012334/

ISI glossary of statistical terms – English-German

error sum of squares - Summe der Fehlerquadrate

http://ec.europa.eu/comm/eurostat/research/index.htm?http://...


Kim Metzger
Mexico
Local time: 07:39
Native speaker of: Native in EnglishEnglish
PRO pts in category: 40
Grading comment
Thanks - especially for all the good references - it was important to include 'sum' here. Thanks to all contributors!

Peer comments on this answer (and responses from the answerer)
agree  Oliver Walter: Yes: as the text says, it's a minimization of the sum of the squares of the errors. "minimization of the sum of the squared errors" would be my translation.
3 hrs
  -> From a man who knows what he's talking about.
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4 hrs   confidence: Answerer confidence 4/5Answerer confidence 4/5 peer agreement (net): +1
least squares minimisation / least squares method


Explanation:
I think least squares minimisation is, if memory serves me correctly, a shorthand way of saying mean-square error minimization which is generally used in linear regression (i.e. selecting the best curve to fit a set of experimental data).
Ycan also refer to least squares regression methods, dropping the minimisation as well.
Ref. "Statistics for technology" Christopher Chatfield, ISBN-10: 0412253402


    Reference: http://en.wikipedia.org/wiki/Least_squares
    Reference: http://en.wikipedia.org/wiki/Linear_regression
Michael Watson
United Kingdom
Local time: 13:39
Works in field
Native speaker of: Native in EnglishEnglish

Peer comments on this answer (and responses from the answerer)
agree  Kim Bakkers: This is how I've heard this called too
15 hrs
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