Model Fitting

Annette J. Dobson
Additional contact information
Annette J. Dobson: University of Newcastle

Chapter 2 in Introduction to Statistical Modelling, 1983, pp 8-20 from Springer

Abstract: Abstract The transmission and reception of information involves a message, or signal, which is distorted by noise. It is sometimes useful to think of scientific data as measurements composed of signal and noise and to construct mathematical models incorporating both of these components. Often the signal is regarded as deterministic (i.e. non-random) and the noise as random. Therefore, a mathematical model of the data combining both signal and noise is probabilistic and it is called a statistical model.

Keywords: Likelihood Function; Maximum Likelihood Estimator; Enrich Environment; Joint Probability Density Function; High Carbohydrate Diet (search for similar items in EconPapers)
Date: 1983
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4899-3174-0_2

Ordering information: This item can be ordered from
http://www.springer.com/9781489931740

DOI: 10.1007/978-1-4899-3174-0_2

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().