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Matrices arising in a discrete-time deterministic model of population growth [[#References|[a3]]]. The Leslie model considers individuals of one sex in a population which is closed to migration. The maximum life span is <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l1200701.png" /> time units, and an individual is said to be in the <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l1200702.png" />th age group if its exact age falls in the interval <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l1200703.png" />, for some <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l1200704.png" />. The corresponding Leslie matrix is given by
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<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l1200705.png" /></td> </tr></table>
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where for each <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l1200706.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l1200707.png" /> is the proportion of individuals in the <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l1200708.png" />th age group who survive one time unit (this is assumed to be positive), and for each <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l1200709.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007010.png" /> is the average number of individuals produced in one time unit by a member of the <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007011.png" />th age group. Let <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007012.png" /> be the average number of individuals in the <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007013.png" />th age group at time <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007014.png" /> units, and let <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007015.png" /> be the vector
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Matrices arising in a discrete-time deterministic model of population growth [[#References|[a3]]]. The Leslie model considers individuals of one sex in a population which is closed to migration. The maximum life span is $k$ time units, and an individual is said to be in the $i$th age group if its exact age falls in the interval $[ i - 1 , i )$, for some $1 \leq i \leq k$. The corresponding Leslie matrix is given by
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007016.png" /></td> </tr></table>
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\begin{equation*} L = \left( \begin{array} { c c c c c } { m _ { 1 } } &amp; { m _ { 2 } } &amp; { \ldots } &amp; { \ldots } &amp; { m _ { k } } \\ { p _ { 1 } } &amp; { 0 } &amp; { \ldots } &amp; { \ldots } &amp; { 0 } \\ { 0 } &amp; { p _ { 2 } } &amp; { 0 } &amp; { \ldots } &amp; { 0 } \\ { \vdots } &amp; { \square } &amp; { \ddots } &amp; { \square } &amp; { \vdots } \\ { 0 } &amp; { \ldots } &amp; { 0 } &amp; { p _ { k - 1 } } &amp; { 0 } \end{array} \right), \end{equation*}
  
Then <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007017.png" />, and since the conditions of mortality and fertility are assumed to persist, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007018.png" /> for each integer <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007019.png" />.
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where for each $1 \leq i \leq k - 1$, $p _ { i }$ is the proportion of individuals in the $i$th age group who survive one time unit (this is assumed to be positive), and for each $1 \leq i \leq k$, $m \quad i$ is the average number of individuals produced in one time unit by a member of the $i$th age group. Let $v _ { i , t }$ be the average number of individuals in the $i$th age group at time $t$ units, and let $v _ { t }$ be the vector
  
If some <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007020.png" /> is positive, then <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007021.png" /> has one positive [[Eigen value|eigen value]] <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007022.png" /> which is a simple root of the [[Characteristic polynomial|characteristic polynomial]]. For any eigenvalue <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007023.png" /> of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007024.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007025.png" />; indeed <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007026.png" /> has exactly <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007027.png" /> eigenvalues of modulus <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007028.png" />, where <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007029.png" /> is the [[Greatest common divisor|greatest common divisor]] of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007030.png" />. Corresponding to the eigenvalue <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007031.png" /> is the right eigenvector <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007032.png" /> given by the formula
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\begin{equation*} \left( \begin{array} { c } { v _ { 1 , t }} \\ { \vdots } \\ { v _ { k , t } } \end{array} \right). \end{equation*}
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007033.png" /></td> </tr></table>
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Then $v _ { t  + 1} = L v_ t $, and since the conditions of mortality and fertility are assumed to persist, $v _ { t } = L ^ { t } v _ { 0 }$ for each integer $t \geq 0$.
  
where <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007034.png" />. A left eigenvector corresponding to <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007035.png" /> has the form <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007036.png" />, where for <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007037.png" />,
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If some $m \quad i$ is positive, then $L$ has one positive [[Eigen value|eigen value]] $r$ which is a simple root of the [[Characteristic polynomial|characteristic polynomial]]. For any eigenvalue $\lambda$ of $L$, $r \geq | \lambda |$; indeed $L$ has exactly $d$ eigenvalues of modulus $r$, where $d$ is the [[Greatest common divisor|greatest common divisor]] of $\{ i : m _ { - } i &gt; 0 \}$. Corresponding to the eigenvalue $r$ is the right eigenvector $w$ given by the formula
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007038.png" /></td> </tr></table>
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\begin{equation*} w = \frac { 1 } { s } \left( \begin{array} { c } { 1 } \\ { p _ { 1 } / r } \\ { p _ { 1 } p _ { 2 } / r ^ { 2 } } \\ { \vdots } \\ { p _ { 1 } \dots p _ { k - 1}  / r ^ { k - 1 } } \end{array} \right), \end{equation*}
  
The quantity <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007039.png" /> is interpreted as the reproductive value of an individual in the <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007040.png" />th age group.
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where $s = 1 + p _ { 1 } / r + \ldots + p _ { 1 } \ldots p _ { k - 1 } / r ^ { k - 1 }$. A left eigenvector corresponding to $r$ has the form $[ y _ { 1 } \ldots y _ { k } ]$, where for $1 \leq j \leq k$,
  
Suppose that there are indices <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007041.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007042.png" /> such that <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007043.png" />, and both <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007044.png" /> and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007045.png" /> are positive. If <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007046.png" />, the sequence of age-distribution vectors, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007047.png" />, is asymptotically periodic as <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007048.png" />, and the period is a divisor of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007049.png" /> depending on <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007050.png" />. When <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007051.png" />, then as <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007052.png" />, the sequence of age-distribution vectors converges to the eigenvector <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007053.png" />, which is called the asymptotic stable age distribution for the population. The nature of the convergence of the age distributions is governed by the quantities <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007054.png" />, where <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007055.png" /> is an eigenvalue of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007056.png" /> distinct from <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007057.png" />; a containment region in the complex plane for these quantities has been characterized (cf. [[#References|[a2]]], [[#References|[a5]]]). The sequence of vectors <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007058.png" /> is asymptotic to <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007059.png" />, where <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007060.png" /> is a positive constant depending on <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007061.png" />; hence <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007062.png" /> is sometimes called the rate of increase for the population. The sensitivity of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007063.png" /> to changes in <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007064.png" /> is discussed in [[#References|[a1]]] and [[#References|[a6]]].
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\begin{equation*} y _ { j } = \sum _ { i = j } ^ { k } p _ { j } \ldots p _ { i - 1 } m _ { i } r ^ { j - i - 1 }. \end{equation*}
  
Variations on the Leslie model include matrix models for populations classified by criteria other than age (see [[#References|[a1]]]), and a model involving a sequence of Leslie matrices changing over time (see [[#References|[a4]]] and [[#References|[a6]]]). A stochastic version of the Leslie model yields a convergence result for the sequence <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007065.png" /> under the hypotheses that <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007066.png" /> and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/l/l120/l120070/l12007067.png" /> (see [[#References|[a6]]]).
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The quantity $y_j$ is interpreted as the reproductive value of an individual in the $j$th age group.
 +
 
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Suppose that there are indices $i$, $j$ such that $1 \leq i \leq j \leq k$, and both $m_j$ and $v _ { i ,0} $ are positive. If $d &gt; 1$, the sequence of age-distribution vectors, $v _ { t } / \sum _ { i = 1 } ^ { k } v _ { i , t }$, is asymptotically periodic as $t \rightarrow \infty$, and the period is a divisor of $d$ depending on $v_0$. When $d = 1$, then as $t \rightarrow \infty$, the sequence of age-distribution vectors converges to the eigenvector $w$, which is called the asymptotic stable age distribution for the population. The nature of the convergence of the age distributions is governed by the quantities $\lambda / r$, where $\lambda$ is an eigenvalue of $L$ distinct from $r$; a containment region in the complex plane for these quantities has been characterized (cf. [[#References|[a2]]], [[#References|[a5]]]). The sequence of vectors $v _ { t }$ is asymptotic to $c r ^ { t } w$, where $c$ is a positive constant depending on $v_0$; hence $r$ is sometimes called the rate of increase for the population. The sensitivity of $r$ to changes in $L$ is discussed in [[#References|[a1]]] and [[#References|[a6]]].
 +
 
 +
Variations on the Leslie model include matrix models for populations classified by criteria other than age (see [[#References|[a1]]]), and a model involving a sequence of Leslie matrices changing over time (see [[#References|[a4]]] and [[#References|[a6]]]). A stochastic version of the Leslie model yields a convergence result for the sequence $v _ { t } / r ^ { t }$ under the hypotheses that $d = 1$ and $r &gt; 1$ (see [[#References|[a6]]]).
  
 
====References====
 
====References====
<table><TR><TD valign="top">[a1]</TD> <TD valign="top">  H. Caswell,  "Matrix population models" , Sinauer  (1989)</TD></TR><TR><TD valign="top">[a2]</TD> <TD valign="top">  K.P. Hadeler,  G. Meinardus,  "On the roots of Cauchy polynomials"  ''Linear Alg. &amp; Its Appl.'' , '''38'''  (1981)  pp. 81–102</TD></TR><TR><TD valign="top">[a3]</TD> <TD valign="top">  P.H. Leslie,  "On the use of matrices in certain population mathematics"  ''Biometrika'' , '''33'''  (1945)  pp. 213–245</TD></TR><TR><TD valign="top">[a4]</TD> <TD valign="top">  N. Keyfitz,  "Introduction to the mathematics of population" , Addison-Wesley  (1977)</TD></TR><TR><TD valign="top">[a5]</TD> <TD valign="top">  S. Kirkland,  "An eigenvalue region for Leslie matrices"  ''SIAM J. Matrix Anal. Appl.'' , '''13'''  (1992)  pp. 507–529</TD></TR><TR><TD valign="top">[a6]</TD> <TD valign="top">  J.H. Pollard,  "Mathematical models for the growth of human populations" , Cambridge Univ. Press  (1973)</TD></TR></table>
+
<table><tr><td valign="top">[a1]</td> <td valign="top">  H. Caswell,  "Matrix population models" , Sinauer  (1989)</td></tr><tr><td valign="top">[a2]</td> <td valign="top">  K.P. Hadeler,  G. Meinardus,  "On the roots of Cauchy polynomials"  ''Linear Alg. &amp; Its Appl.'' , '''38'''  (1981)  pp. 81–102</td></tr><tr><td valign="top">[a3]</td> <td valign="top">  P.H. Leslie,  "On the use of matrices in certain population mathematics"  ''Biometrika'' , '''33'''  (1945)  pp. 213–245</td></tr><tr><td valign="top">[a4]</td> <td valign="top">  N. Keyfitz,  "Introduction to the mathematics of population" , Addison-Wesley  (1977)</td></tr><tr><td valign="top">[a5]</td> <td valign="top">  S. Kirkland,  "An eigenvalue region for Leslie matrices"  ''SIAM J. Matrix Anal. Appl.'' , '''13'''  (1992)  pp. 507–529</td></tr><tr><td valign="top">[a6]</td> <td valign="top">  J.H. Pollard,  "Mathematical models for the growth of human populations" , Cambridge Univ. Press  (1973)</td></tr></table>

Revision as of 15:30, 1 July 2020

Matrices arising in a discrete-time deterministic model of population growth [a3]. The Leslie model considers individuals of one sex in a population which is closed to migration. The maximum life span is $k$ time units, and an individual is said to be in the $i$th age group if its exact age falls in the interval $[ i - 1 , i )$, for some $1 \leq i \leq k$. The corresponding Leslie matrix is given by

\begin{equation*} L = \left( \begin{array} { c c c c c } { m _ { 1 } } & { m _ { 2 } } & { \ldots } & { \ldots } & { m _ { k } } \\ { p _ { 1 } } & { 0 } & { \ldots } & { \ldots } & { 0 } \\ { 0 } & { p _ { 2 } } & { 0 } & { \ldots } & { 0 } \\ { \vdots } & { \square } & { \ddots } & { \square } & { \vdots } \\ { 0 } & { \ldots } & { 0 } & { p _ { k - 1 } } & { 0 } \end{array} \right), \end{equation*}

where for each $1 \leq i \leq k - 1$, $p _ { i }$ is the proportion of individuals in the $i$th age group who survive one time unit (this is assumed to be positive), and for each $1 \leq i \leq k$, $m \quad i$ is the average number of individuals produced in one time unit by a member of the $i$th age group. Let $v _ { i , t }$ be the average number of individuals in the $i$th age group at time $t$ units, and let $v _ { t }$ be the vector

\begin{equation*} \left( \begin{array} { c } { v _ { 1 , t }} \\ { \vdots } \\ { v _ { k , t } } \end{array} \right). \end{equation*}

Then $v _ { t + 1} = L v_ t $, and since the conditions of mortality and fertility are assumed to persist, $v _ { t } = L ^ { t } v _ { 0 }$ for each integer $t \geq 0$.

If some $m \quad i$ is positive, then $L$ has one positive eigen value $r$ which is a simple root of the characteristic polynomial. For any eigenvalue $\lambda$ of $L$, $r \geq | \lambda |$; indeed $L$ has exactly $d$ eigenvalues of modulus $r$, where $d$ is the greatest common divisor of $\{ i : m _ { - } i > 0 \}$. Corresponding to the eigenvalue $r$ is the right eigenvector $w$ given by the formula

\begin{equation*} w = \frac { 1 } { s } \left( \begin{array} { c } { 1 } \\ { p _ { 1 } / r } \\ { p _ { 1 } p _ { 2 } / r ^ { 2 } } \\ { \vdots } \\ { p _ { 1 } \dots p _ { k - 1} / r ^ { k - 1 } } \end{array} \right), \end{equation*}

where $s = 1 + p _ { 1 } / r + \ldots + p _ { 1 } \ldots p _ { k - 1 } / r ^ { k - 1 }$. A left eigenvector corresponding to $r$ has the form $[ y _ { 1 } \ldots y _ { k } ]$, where for $1 \leq j \leq k$,

\begin{equation*} y _ { j } = \sum _ { i = j } ^ { k } p _ { j } \ldots p _ { i - 1 } m _ { i } r ^ { j - i - 1 }. \end{equation*}

The quantity $y_j$ is interpreted as the reproductive value of an individual in the $j$th age group.

Suppose that there are indices $i$, $j$ such that $1 \leq i \leq j \leq k$, and both $m_j$ and $v _ { i ,0} $ are positive. If $d > 1$, the sequence of age-distribution vectors, $v _ { t } / \sum _ { i = 1 } ^ { k } v _ { i , t }$, is asymptotically periodic as $t \rightarrow \infty$, and the period is a divisor of $d$ depending on $v_0$. When $d = 1$, then as $t \rightarrow \infty$, the sequence of age-distribution vectors converges to the eigenvector $w$, which is called the asymptotic stable age distribution for the population. The nature of the convergence of the age distributions is governed by the quantities $\lambda / r$, where $\lambda$ is an eigenvalue of $L$ distinct from $r$; a containment region in the complex plane for these quantities has been characterized (cf. [a2], [a5]). The sequence of vectors $v _ { t }$ is asymptotic to $c r ^ { t } w$, where $c$ is a positive constant depending on $v_0$; hence $r$ is sometimes called the rate of increase for the population. The sensitivity of $r$ to changes in $L$ is discussed in [a1] and [a6].

Variations on the Leslie model include matrix models for populations classified by criteria other than age (see [a1]), and a model involving a sequence of Leslie matrices changing over time (see [a4] and [a6]). A stochastic version of the Leslie model yields a convergence result for the sequence $v _ { t } / r ^ { t }$ under the hypotheses that $d = 1$ and $r > 1$ (see [a6]).

References

[a1] H. Caswell, "Matrix population models" , Sinauer (1989)
[a2] K.P. Hadeler, G. Meinardus, "On the roots of Cauchy polynomials" Linear Alg. & Its Appl. , 38 (1981) pp. 81–102
[a3] P.H. Leslie, "On the use of matrices in certain population mathematics" Biometrika , 33 (1945) pp. 213–245
[a4] N. Keyfitz, "Introduction to the mathematics of population" , Addison-Wesley (1977)
[a5] S. Kirkland, "An eigenvalue region for Leslie matrices" SIAM J. Matrix Anal. Appl. , 13 (1992) pp. 507–529
[a6] J.H. Pollard, "Mathematical models for the growth of human populations" , Cambridge Univ. Press (1973)
How to Cite This Entry:
Leslie matrix. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Leslie_matrix&oldid=14442
This article was adapted from an original article by S. Kirkland (originator), which appeared in Encyclopedia of Mathematics - ISBN 1402006098. See original article