Confidence intervals versus regions

TL;DR: The 25-page Bibliography in Applied Regression Analysis, 2nd edition, by N.R Draper and H. Smith, published by Wiley in 1981, was previously extended by a list of selected references available during 1988-89,1990-91 and 1992-93, plus a few older references.

TL;DR: The program, coded in the computer algebra package MAPLE, has been used in a graduate level class in response surface methodology (RSM), and three examples taken from the literature illustrate the use and features of the program.

TL;DR: In the development of this protocol all of the steps for parameter estimation will be revisited: parameter sensitivity analysis, statistical design of experiments, estimation of parameters and confidence regions, by considering all these steps as a whole the overall parameter estimation procedure can be more efficient and some pitfalls may be dealt with in an appropriate manner.

TL;DR: In this article, a general nonlinear parameter estimation problem was formulated to identify the kinetic parameters involved in the developed ALD gas-surface reaction mechanism, governing ZnO film growth, from ex situ film thickness measurements.

Abstract: The title compound, [Zn(C8H10F3O2)2(CH4O)2], is a dimethanol coordinated zinc complex with the acetyl acetonate derivative 1,1,1-trifluoro-5,5-dimethylhexane-2,4-dionate. The bis-β-diketonate complex, which is isostructural with its Co analogue, is located on a crystallographic inversion center. The complex is octahedral with basically no distortion, and the methanol molecules are in trans positions with respect to one another. The planes of the β-diketonate and the ZnO4 unit are tilted by 18.64 (10)° against each other. O—H⋯O hydrogen bonds between the methanol hydroxyl groups and neighboring diketonate O atoms create chains running along [100].

TL;DR: In this article, the authors present a Second-Order Response Surface Methodology (SRSM) for response surface design, which is based on Maxima and Ridge systems with second-order response surfaces.

TL;DR: In this paper, the authors present a method to estimate the least squares of a scatterplot matrix using a simple linear regression model, and compare it with the mean function of the scatterplot matrices.