Our system is currently under heavy load due to increased usage. We're actively working on upgrades to improve performance. Thank you for your patience.
1945
DOI: 10.1093/biomet/33.3.183
|View full text |Cite
|
Sign up to set email alerts
|

On the Use of Matrices in Certain Population Mathematics

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

2
861
0
46

Year Published

1996
1996
2016
2016

Publication Types

Select...
6
2

Relationship

0
8

Authors

Journals

citations
Cited by 2,352 publications
(909 citation statements)
references
References 2 publications
2
861
0
46
Order By: Relevance
“…Certainly, the same values from Table 3 would be obtained in any census carried out in the stationary part of the series at exact times t, t + 1, etc. These observations lead to the following conclusion: If a finite stationary population is observed at regular time-intervals, and age and life left are grouped at intervals of 5 The same approach is used in matrix population models, in which one also considers an age-classified population, and defines the projection matrix ('Leslie matrix') from exact time t to exact time t + 1 for each age class (Caswell 2001;Leslie 1945) the same width, then the Brouard-Carey equality may hold. A more formal statement is presented in the following section.…”
Section: The Discrete-time Frameworkmentioning
confidence: 99%
See 1 more Smart Citation
“…Certainly, the same values from Table 3 would be obtained in any census carried out in the stationary part of the series at exact times t, t + 1, etc. These observations lead to the following conclusion: If a finite stationary population is observed at regular time-intervals, and age and life left are grouped at intervals of 5 The same approach is used in matrix population models, in which one also considers an age-classified population, and defines the projection matrix ('Leslie matrix') from exact time t to exact time t + 1 for each age class (Caswell 2001;Leslie 1945) the same width, then the Brouard-Carey equality may hold. A more formal statement is presented in the following section.…”
Section: The Discrete-time Frameworkmentioning
confidence: 99%
“…However, in matrix population models, death probabilities -or the analogous survival probabilities -usually refer to the period-cohort Lexis parallelogram, instead of the age-cohort parallelogram. For instance, the elements of the sub-diagonal of the Leslie matrix are the probabilities that an individual with age [x, x + 1) at exact time t will be alive in age group [x + 1, x + 2) at exact time t + 1 (Caswell 2001;Leslie 1945). 7 For time-intervals of length n = 1, the conversion from death rates m x to death probabilities is given by q x = m x /(1 − (1 − a x ) · m x ), assuming m x is represented by a step function.…”
Section: Proofmentioning
confidence: 99%
“…where m is a vector of immigrants (with age-sex elements corresponding to those of n, all nonnegative) and Q is a 10×10 Leslie matrix (Leslie, 1945(Leslie, , 1948; its nonzero elements are determined by age-sex-specific survival rates, the fertility rate, and the male/female birth ratio. If there were no immigration, and all rates were constant,…”
Section: The Modelmentioning
confidence: 99%
“…Such populations are described by stage-classified demographic models, of which the age-classified theory is a special case. Stage-classified demography can be analyzed using matrix population models (Leslie 1945;Caswell 2001); see Section B. The discrete-time population growth rate λ is the dominant eigenvalue of the population projection matrix A (guaranteed to be real and positive by the Perron-Frobenius theorem; Caswell 2001).…”
Section: Stage-classified Populationsmentioning
confidence: 99%
“…To compare (24) with Hamilton's results (1) and (2), consider an age-classified matrix (a Leslie matrix) with fertilities F i in the first row, survival probabilities P i on the subdiagonal, and zeros elsewhere (Leslie 1945;Keyfitz 1968). In this case (24) simplifies to…”
Section: Age-classified Models As a Special Casementioning
confidence: 99%