Add to ORKGThis thesis consists of six papers related to saturated orthogonal designs, spectroscopic and high dimension data analysis. The first two papers deals with testing procedures for saturated orthogonal designs. Both the presented methods controls the multiple level of significance. In paper C a regression method is constructed for both multivariate and univariate situations. The correctness of the subspace of regression can be tested using the multiple testing technique constructed in paper A. Paper D gives a method for testing the chemical rank of spectroscopic data. In paper E the effectiveness of high-dimension data gathered in a random way is examined and compared to an optimality criteria. Paper F deals with partial least squares and cro...
This thesis focuses particularly on the application of chemometrics in the field of analytical che...
Optimized operating conditions for complex systems can be attained by using advanced combinations of...
Experiments on patients, processes or plants all have random error, making statistical methods essen...
This thesis consists of six papers related to saturated orthogonal designs, spectroscopic and high d...
Modern methods of the experimental data collection, storage and processing require building an inter...
Although three-level factorial designs with quantitative factors are not the most efficient way to f...
A general procedure is described for examining the significance of effects in experiments utilizing ...
A method of variable selection for use with orthogonally designed calibration data sets, such as fac...
The book provides necessary knowledge for readers interested in developing the theory of uniform exp...
This chapter gives a survey on the use of statistical designs for what-if analysis in simula- tion, ...
The ability of a chromatographic method to successfully separate, identify and quantitative species ...
Statistical design of experiments allows for multiple factors influencing a process to be systematic...
Factorial designs are very important when experiments involve two or more factors and it is desirabl...
Some general remarks for experimental designs are made. The general statistical methodology of analy...
Using linear algebra this thesis developed linear regression analysis including analysis of variance...
This thesis focuses particularly on the application of chemometrics in the field of analytical che...
Optimized operating conditions for complex systems can be attained by using advanced combinations of...
Experiments on patients, processes or plants all have random error, making statistical methods essen...
This thesis consists of six papers related to saturated orthogonal designs, spectroscopic and high d...
Modern methods of the experimental data collection, storage and processing require building an inter...
Although three-level factorial designs with quantitative factors are not the most efficient way to f...
A general procedure is described for examining the significance of effects in experiments utilizing ...
A method of variable selection for use with orthogonally designed calibration data sets, such as fac...
The book provides necessary knowledge for readers interested in developing the theory of uniform exp...
This chapter gives a survey on the use of statistical designs for what-if analysis in simula- tion, ...
The ability of a chromatographic method to successfully separate, identify and quantitative species ...
Statistical design of experiments allows for multiple factors influencing a process to be systematic...
Factorial designs are very important when experiments involve two or more factors and it is desirabl...
Some general remarks for experimental designs are made. The general statistical methodology of analy...
Using linear algebra this thesis developed linear regression analysis including analysis of variance...
This thesis focuses particularly on the application of chemometrics in the field of analytical che...
Optimized operating conditions for complex systems can be attained by using advanced combinations of...
Experiments on patients, processes or plants all have random error, making statistical methods essen...