Course detail
Empiric Models
FSI-9EMMAcad. year: 2024/2025
If the important variables for a process are known or sought but the process model is unknown, an empirical approach to model building is required. The development of empirical models represents a continuous process that involves postulation of a model, experimentation to collect empirical data, "fitting" of the model, i.e. estimation of the model coefficients, and evaluation of results. The strategy of empirical model building is described in the course.
Language of instruction
Mode of study
Guarantor
Department
Entry knowledge
Rules for evaluation and completion of the course
Aims
Empiric model, fitting, residuum, adequate model
Study aids
Prerequisites and corequisites
Basic literature
D. M. Himmelblau: Process Analysis by Statistical Methods. John Wiley&Sons,New York 1969
K. Zvára: Regresní analýza. Academia, Praha 1989
Vícerozměrné statistické metody: Vícerozměrné statistické metody. SNTL/ALFA, Praha 1987
Recommended reading
J. Anděl_: Matematická statistika. SNTL/ALFA, Praha 1978
K. Zvára: Vícerozměrné statistické metody. SNTL/ALFA, Praha 1987
Elearning
Classification of course in study plans
- Programme D-APM-P Doctoral 1 year of study, winter semester, recommended course
- Programme D-KPI-P Doctoral 1 year of study, winter semester, recommended course
- Programme D-APM-K Doctoral 1 year of study, winter semester, recommended course
- Programme D-KPI-K Doctoral 1 year of study, winter semester, recommended course
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
2. Linear models with one independent variable. Least squares estimation.
3. Analysis of variance. Variances of parameters.
4. Variances of predicted values.
5. ANOVA about the adequate model.
6. Confidence intervals for parameters.
7. Locus of confidence limits.
8. Locus of tolerance limits.
9. Confidence region.
10.Linear models with several independent variables.
11.Reziduals.
Elearning