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regression analysis

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Published: 01 December 2009
Fig. 5 Posttraining linear regression analysis between experimental data (horizontal axis, T values) and neural-network predictions (vertical axis, A values). The diagonal dashed line is A = T. (a) and (c) Training datasets. (b) and (d) Testing datasets. Levenberg-Marquardt training alone More
Image
Published: 01 January 2000
Fig. 5 Analysis of variance procedure of linear regression More
Series: ASM Handbook
Volume: 8
Publisher: ASM International
Published: 01 January 2000
DOI: 10.31399/asm.hb.v08.a0009216
EISBN: 978-1-62708-176-4
.... The article presents statistical methods which help in determining design allowables. These methods include direct computation for normal distribution, direct computation for an unknown distribution, computation of derived properties, and regression analysis. The article concludes with information on low...
Series: ASM Handbook
Volume: 8
Publisher: ASM International
Published: 01 January 2000
DOI: 10.31399/asm.hb.v08.a0009218
EISBN: 978-1-62708-176-4
... and the rational polynomial creep equation are discussed. The article also describes the dependence of stress and temperature on equation parameters and explains the lot-centered regression analysis. creep creep-rupture data exponential creep lot-centered regression analysis rational polynomial creep...
Series: ASM Handbook
Volume: 13A
Publisher: ASM International
Published: 01 January 2003
DOI: 10.31399/asm.hb.v13a.a0003712
EISBN: 978-1-62708-182-5
... regression are also illustrated. statistical analysis confidence limits sampling issue analysis of variance correlation regression corrosionist statistical hypothesis testing THIS ARTICLE is an overview of basic statistical inference and reviews several of the most commonly used statistical...
Image
Published: 01 January 2000
Fig. 23 Plot of measured stress/strain pairs and the equation obtained for regression analysis. Region with large changes in friction conditions at support edges is magnified. More
Series: ASM Handbook
Volume: 20
Publisher: ASM International
Published: 01 January 1997
DOI: 10.31399/asm.hb.v20.a0002431
EISBN: 978-1-62708-194-8
... the basic statistical procedures that can be used to address variability and uncertainty in an engineering analysis. It contains a table that lists the relevant statistics standards published by the American Society of Testing and Materials. data-regression dscrete distributions goodness-of-fit test...
Series: ASM Handbook
Volume: 13A
Publisher: ASM International
Published: 01 January 2003
DOI: 10.31399/asm.hb.v13a.a0003708
EISBN: 978-1-62708-182-5
... hypotheses and selection of statistical tests. Illustrations are given of specific statistical tests and the concept of confidence limits. It concludes with a discussion of sampling issues, one- way analysis of variance, correlation, and simple regression analysis. Materials The article “Materials...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005407
EISBN: 978-1-62708-196-2
... particular combination of database distribution, architecture, training algorithm, and transfer function can be tested by an analysis of the network response in a form of linear regression between network outputs (predictions) and corresponding targets (experimental data) for the training and testing...
Series: ASM Handbook
Volume: 5
Publisher: ASM International
Published: 01 January 1994
DOI: 10.31399/asm.hb.v05.a0001295
EISBN: 978-1-62708-170-2
... of the calculated spectrum versus the measured spectrum. Other advanced features include regression analysis of thicknesses and optical constants for multiple films and extended wavelength ranges. Spectral Interpretation The equipment is basically an interferometer that scans wavelength for a fixed...
Series: ASM Handbook
Volume: 8
Publisher: ASM International
Published: 01 January 2000
DOI: 10.31399/asm.hb.v08.a0009215
EISBN: 978-1-62708-176-4
... multivariate analysis methods ( Ref 10 , 11 ), nonparametric methods ( Ref 12 , 13 ), and regression analysis problems ( Ref 14 , 15 , 16 ). Many statistical procedures can also be easily applied using computer software ( Ref 17 , 18 ). Four types of designed experiments are analyzed in this article...
Series: ASM Handbook
Volume: 8
Publisher: ASM International
Published: 01 January 2000
DOI: 10.31399/asm.hb.v08.a0009212
EISBN: 978-1-62708-176-4
... statistical procedures that can be applied to mechanical property data. Correlation and regression analysis is dealt with briefly, followed by a discussion of the analysis of designed experiments. In this article in particular, sources of further information are given. Data-specific analysis methods...
Series: ASM Handbook
Volume: 21
Publisher: ASM International
Published: 01 January 2001
DOI: 10.31399/asm.hb.v21.a0003386
EISBN: 978-1-62708-195-5
... of the mechanics based model, the regression algorithm, and the semi-empirical analysis. composites damage tolerance military aircraft metallic structures composite structures regression algorithm durability semi-empirical analysis THE DAMAGE TOLERANCE DESIGN PHILOSOPHY has been required on all...
Series: ASM Handbook
Volume: 4A
Publisher: ASM International
Published: 01 August 2013
DOI: 10.31399/asm.hb.v04a.a0005796
EISBN: 978-1-62708-165-8
..., with calculation examples for 8645 steel and 86B45 steel. boron steel carbon content carbon steel hardenability low-alloy steel regression analysis Introduction Hardenability of steel is the property that determines the depth and distribution of hardness induced by quenching. The extent...
Image
Published: 01 January 1994
Fig. 4 Measurement and analysis of surface damage using x-ray diffraction. (a) 38 mm (1.5 in.) 1018 steel cutoff sample showing burn-related discoloration. Two residual stress measurements by x-ray diffraction were made on the sample at the locations marked by the four concentric markers. (b More
Series: ASM Handbook
Volume: 13A
Publisher: ASM International
Published: 01 January 2003
DOI: 10.31399/asm.hb.v13a.a0003641
EISBN: 978-1-62708-182-5
... programs are: Population, sample, and replication Best estimate of variance and standard deviation Confidence limits for the mean Simple linear regression Multiple regression analysis and analysis of variance Covariance of independent variables A long list of secondary topics...
Series: ASM Handbook
Volume: 19
Publisher: ASM International
Published: 01 January 1996
DOI: 10.31399/asm.hb.v19.a0002369
EISBN: 978-1-62708-193-1
... as such in the regression analysis. To treat cycles as the independent variable can lead to errors in the regression ( Ref 19 ). Fig. 2 Schematic of S - N curve With the median value of life determined for all effective stress amplitudes, it is left to determine how much variation about that line is present...
Book Chapter

By Eugene Shapiro
Series: ASM Handbook
Volume: 8
Publisher: ASM International
Published: 01 January 2000
DOI: 10.31399/asm.hb.v08.a0003268
EISBN: 978-1-62708-176-4
... are described extensively in this article with greater emphasis on interpretation and analysis. Also included are descriptions of methods used in Europe and Japan. Finally, a section on computerized testing is included. Bending tests that have been developed for brittle materials, coatings, construction...
Series: ASM Handbook
Volume: 22A
Publisher: ASM International
Published: 01 December 2009
DOI: 10.31399/asm.hb.v22a.a0005416
EISBN: 978-1-62708-196-2
... models and in the treatment of noise and uncertainties. It is now well established that the method is not only capable of representing known data but can also lead to the discovery of novel concepts ( Ref 1 to 2 ). To begin, the method is introduced. The Method In regression analysis, the data...
Series: ASM Handbook
Volume: 8
Publisher: ASM International
Published: 01 January 2000
DOI: 10.31399/asm.hb.v08.a0009219
EISBN: 978-1-62708-176-4
... a regression analysis is performed on a collection of fatigue data, it is generally assumed that the observations are independent and randomized. This set of assumptions is seldom the case, however, and can lead to confusing or invalid conclusions. For example, assume that fatigue data are available from...