Explore: Goodness Of Fit
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Books Results
Source: The Open Library
The Open Library Search Results
Search results from The Open Library
1Nonparametric smoothing and lack-of-fit tests
By Jeffrey D. Hart
“Nonparametric smoothing and lack-of-fit tests” Metadata:
- Title: ➤ Nonparametric smoothing and lack-of-fit tests
- Author: Jeffrey D. Hart
- Language: English
- Number of Pages: Median: 288
- Publisher: Springer - Springer New York
- Publish Date: 1997 - 2012
- Publish Location: New York
“Nonparametric smoothing and lack-of-fit tests” Subjects and Themes:
- Subjects: ➤ Nonparametric statistics - Smoothing (Statistics) - Goodness-of-fit tests - GOODNESS OF FIT - Test d'ajustement (Statistiques) - Inferencia nao parametrica - Statistique non parametrique - SMOOTHING - Gute der Anpassung - Lissage (Statistique) - STATISTICAL TESTS - Estatistica - Regressionsmodell - Ajustement, Tests d' (Statistiques) - Nichtparametrisches Verfahren - Methodes statistiques - Statistique non-parametrique - Statistics - Statistics, general
Edition Identifiers:
- The Open Library ID: OL37165460M - OL665310M
- Online Computer Library Center (OCLC) ID: 36543504
- Library of Congress Control Number (LCCN): 97010931
- All ISBNs: 9781475727241 - 0387949801 - 1475727240 - 9780387949802
Access and General Info:
- First Year Published: 1997
- Is Full Text Available: No
- Is The Book Public: No
- Access Status: No_ebook
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2Parameter estimation techniques based on optimizing goodness-of-fit statistics for structural reliability
By Alois Starlinger
“Parameter estimation techniques based on optimizing goodness-of-fit statistics for structural reliability” Metadata:
- Title: ➤ Parameter estimation techniques based on optimizing goodness-of-fit statistics for structural reliability
- Author: Alois Starlinger
- Language: English
- Publisher: ➤ National Aeronautics and Space Administration - National Technical Information Service, distributor - American Society of Mechanical Engineers
- Publish Date: 1993
- Publish Location: ➤ [Easton, Pa.?] - Springfield, Va - [Washington, DC
“Parameter estimation techniques based on optimizing goodness-of-fit statistics for structural reliability” Subjects and Themes:
- Subjects: ➤ Goodness of fit - Structural reliability - Weibull density functions - Parameter identification - Statistical tests - Ceramics
Edition Identifiers:
- The Open Library ID: OL15420574M
Access and General Info:
- First Year Published: 1993
- Is Full Text Available: No
- Is The Book Public: No
- Access Status: No_ebook
Online Access
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Wiki
Source: Wikipedia
Wikipedia Results
Search Results from Wikipedia
Goodness of fit
The goodness of fit of a statistical model describes how well it fits a set of observations. Measures of goodness of fit typically summarize the discrepancy
Chi-squared test
method of statistical analysis consisting of using the Pearson distribution to model the observation and performing a test of goodness of fit to determine
Logistic regression
the sum of the squared deviations of the fit from the data points (yk), the squared error loss, is taken as a measure of the goodness of fit, and the
Hosmer–Lemeshow test
The Hosmer–Lemeshow test is a statistical test for goodness of fit and calibration for logistic regression models. It is used frequently in risk prediction
Confirmatory factor analysis
0 to 1, with a value of .08 or less being indicative of an acceptable model. The goodness of fit index (GFI) is a measure of fit between the hypothesized
Pearson's chi-squared test
to assess three types of comparison: goodness of fit, homogeneity, and independence. A test of goodness of fit establishes whether an observed frequency
Kolmogorov–Smirnov test
of the two samples. The Kolmogorov–Smirnov test can be modified to serve as a goodness of fit test. In the special case of testing for normality of the
Regression validation
analysis, are acceptable as descriptions of the data. The validation process can involve analyzing the goodness of fit of the regression, analyzing whether the
Coefficient of determination
also proved more robust for poor fits compared to SMAPE on certain test datasets. When evaluating the goodness-of-fit of simulated (Ypred) versus measured
G-test
(exact test of goodness-of-fit, Fisher's exact test) if the total sample size is less than 1 000 . There is nothing magical about a sample size of 1 000, it's