Access the full text.
Sign up today, get DeepDyve free for 14 days.
R. Pitt-Rivers (1960)
SOME FACTORS THAT AFFECT THYROID HORMONE SYNTHESISAnnals of the New York Academy of Sciences, 86
E. Hewitt, K. Stromberg (1967)
Real And Abstract Analysis
G. Gavalas (1968)
Nonlinear Differential Equations of Chemically Reacting Systems
C. Ridler-Rowe, H. Tucker (1968)
A Graduate Course in Probability, 131
J. Kittrell, R. Mezaki, C. Watson (1965)
ESTIMATION OF PARAMETERS FOR NONLINEAR LEAST SQUARES ANALYSISIndustrial & Engineering Chemistry, 57
C. Tsokos (1969)
On a stochastic integral equation of the Volterra typeMathematical systems theory, 3
A. Blanc-Lapierre, R. Fortet (1965)
Theory of random functions
B. Stevens (1965)
Chemical kinetics
E. Lee (1968)
Quasilinearization and Estimation of Parameters in Differential EquationsIndustrial & Engineering Chemistry Fundamentals, 7
D. Mcquarrie (1967)
Stochastic approach to chemical kineticsJournal of Applied Probability, 4
G. Box (1960)
FITTING EMPIRICAL DATA *Annals of the New York Academy of Sciences, 86
H. Ahrens (1973)
CHUNG, K. L.: A course in probability theory. Harcourt & Brace, New York 1968. VIII, 331 S.Biometrische Zeitschrift, 15
K. Chung (1949)
A Course in Probability Theory
R. Livingston (1939)
Physics chemical experiments
Bartle, R. Gardner (1968)
The Elements Of IntegrationAmerican Mathematical Monthly, 75
R. Aris (1965)
Introduction to the Analysis of Chemical Reactors
J. Horvath (1966)
Topological vector spaces and distributions
M. Landsberg (1966)
E. Hewitt and K. Stromberg, Real and Abstract Analysis. VIII + 476 S. m. 8 Abb. Berlin/Heidelberg/New York 1965. Springer-Verlag. Preis geb. DM 38,—Zamm-zeitschrift Fur Angewandte Mathematik Und Mechanik, 46
K. Yosida (1965)
Functional analysis
L. G. Parrott (1961)
Probability and experimental errors
Acta Biotheoretica XXlII (i): I8-34 (1974) by SUSAN MILTON AND CHRIS P. TSOKOS Radford College and University of South Florida (received I5-XI-I973) I. INTRODUCTION In many instances in the physical and biological sciences mathematical models are used in an attempt to describe or explain tile complex pro- cesses under consideration. These models are usually deterministic in nature but are generally arrived at by experimental techniques. They frequently involve functions which are assumed to be of a fixed but unknown nature and which must be approximated and constants which have a specific physical meaning but whose values must be obtained using laboratory techniques. The usual method for approximating an unknown function x(t) is to obtain experimentally at various times h several values for x(h) and then use as the "true" value of x(h) some estimate based on these observations, usually the mean. By taking points h sufficiently close together an approximating curve for x(t) is constructed and is used as the "true" form of x(t) in subsequent calculations. A similar technique is used to obtain the value to be used for any unknown constant K which appears in the model. If this procedure were repeated many times, even under the
Acta Biotheoretica – Springer Journals
Published: Apr 16, 2005
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.