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Robust Response Surfaces, Regression, and Positive Data Analyses

Rabindra Nath Das
€137.99
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A01=Rabindra Nath Das
advanced experimental statistics
Age Group_Uncategorized
Age Group_Uncategorized
Author_Rabindra Nath Das
autocorrelated
Autocorrelated Error Structure
Autocorrelated Structure
automatic-update
Category1=Non-Fiction
Category=KJMV5
Category=PBT
Category=PDE
Category=PS
Category=TBC
Category=TQ
Compound Symmetry
Compound Symmetry Structure
COP=United States
correlate
correlated
correlated data analysis
Correlated Error
Correlated Error Structure
Correlated Regression Models
correlation
Correlation Structure
Delivery_Pre-order
designs
Dual Response Approach
eq_bestseller
eq_isMigrated=0
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
error
experimental design optimization
GA Fit
Gamma Models
Homoscedastic Errors
Intra-class Structure
Language_English
lifetime data modeling
Lifetime Distribution
LN Model
matrix
methodology
methods for estimating model parameters
moment
Non-constant Variances
Normal Probability Plot
PA=Temporarily unavailable
Price_€100 and above
PS=Active
Quality Improvement Experiments
regression and positive data analysis techniques
Regression Design
Response Surface Designs
response surface methodology (RSM)
robust regression for scientific experiments
robust response surface methodology (RRSM)
Robust Rotatable
Rotatable Designs
RRSM in experimental designs
softlaunch
statistical modeling techniques
structure
Tri-diagonal Structure
Tridiagonal Structure
Variance Covariance Structure
variance estimation methods

Product details

  • ISBN 9781466506770
  • Weight: 780g
  • Dimensions: 178 x 254mm
  • Publication Date: 21 May 2014
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
  • Language: English
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Description

Although widely used in science and technology for experimental data generating, modeling, and optimization, the response surface methodology (RSM) has many limitations. Showing how robust response surface methodology (RRSM) can overcome these limitations, Robust Response Surfaces, Regression, and Positive Data Analyses presents RRS designs, along with the relevant regression and positive data analysis techniques. It explains how to use RRSM in experimental designs and regression analysis.

The book addresses problems of RRS designs, such as rotatability, slope-rotatability, weak rotatability, and optimality. It describes methods for estimating model parameters as well as positive data analysis techniques. The author illustrates the concepts and methods with real examples of lifetime responses, resistivity, replicated measures, and more.

The range of topics and applications gives the book broad appeal both to theoreticians and practicing professionals. The book helps quality engineers, scientists in any area, medical practitioners, demographers, economists, and statisticians understand the theory and applications of RRSM. It can also be used in a second course on the design of experiments.

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