objective_fun

internal

Fit the most popular human mortality 'laws', and construct
full and abridge life tables given various input indices. A mortality
law is a parametric function that describes the dying-out process of
individuals in a population during a significant portion of their
life spans. For a comprehensive review of the most important mortality
laws see Tabeau (2001) <doi:10.1007/0-306-47562-6_1>.
Practical functions for downloading data from various human mortality
databases are provided as well.

Marius Pascariu

MortalityLaws

Parametric Mortality Models, Life Tables and HMD

Marius D. Pascariu

Vladimir Canudas-Romo

objective_fun function

<dl><dt>x</dt>
<dd>Vector of ages at the beginning of the age interval.</dd>
<dt>Dx</dt>
<dd>Object containing death counts. An element of the <code>Dx</code> object
represents the number of deaths during the year to persons aged x to x+n.</dd>
<dt>Ex</dt>
<dd>Exposure in the period. <code>Ex</code> can be approximated by the
mid-year population aged x to x+n.</dd>
<dt>mx</dt>
<dd>Life table death rate in age interval [x, x+n).</dd>
<dt>qx</dt>
<dd>Probability of dying in age interval [x, x+n).</dd>
<dt>law</dt>
<dd>The name of the mortality law/model to be used. e.g.
<code>gompertz</code>, <code>makeham</code>, ... To investigate all the possible options,
see <code>availableLaws</code> function.</dd>
<dt>opt.method</dt>
<dd>How would you like to find the parameters? Specify the
function to be optimize. Available options: the Poisson likelihood function
<code>poissonL</code>; the Binomial likelihood function -<code>binomialL</code>; and
6 other loss functions. For more details, check the <code>availableLF</code>
function.</dd>
<dt>custom.law</dt>
<dd>Allows you to fit a model that is not defined
in the package. Accepts as input a function.</dd></dl>

Arguments

Function to be Optimize — objective_fun

<dl>

<dt>x</dt>
<dd>Vector of ages at the beginning of the age interval.</dd>


<dt>Dx</dt>
<dd>Object containing death counts. An element of the <code>Dx</code> object
represents the number of deaths during the year to persons aged x to x+n.</dd>


<dt>Ex</dt>
<dd>Exposure in the period. <code>Ex</code> can be approximated by the
mid-year population aged x to x+n.</dd>


<dt>mx</dt>
<dd>Life table death rate in age interval [x, x+n).</dd>


<dt>qx</dt>
<dd>Probability of dying in age interval [x, x+n).</dd>


<dt>law</dt>
<dd>The name of the mortality law/model to be used. e.g.
<code>gompertz</code>, <code>makeham</code>, ... To investigate all the possible options,
see <code>availableLaws</code> function.</dd>


<dt>opt.method</dt>
<dd>How would you like to find the parameters? Specify the
function to be optimize. Available options: the Poisson likelihood function
<code>poissonL</code>; the Binomial likelihood function -<code>binomialL</code>; and
6 other loss functions. For more details, check the <code>availableLF</code>
function.</dd>


<dt>custom.law</dt>
<dd>Allows you to fit a model that is not defined
in the package. Accepts as input a function.</dd>

</dl>

objective_fun: Function to be Optimize

Description

Usage

Value

Arguments