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Documentation_Parametric_Bootstrap_V3_update 2014-07-25.pdf
Parametric Bootstrap or Resample a projection matrix documentation
<p>This documentation (tutorial to run the workflow) explains how to run a workflow that belongs to the pack with same name.</p><p>The Parametric Bootstrap or Resample a projection matrix Workflow provides an environment to resample a projection matrix using a multinomial distribution for transitions and a log normal distribution for fertilities (Stubben, Milligan, and Nantel. 2011). The resample is based on number of plants surveyed. The projection matrix A is first split into separate transition and fertility matrices. Dead fates are added to the transition matrix and the columns are then sampled from a Multinomial distribution based on the size in each corresponding stage class in n. The fertility rates are sample from a Log Normal distribution using the lnorms function. The same variance is applied to all rates by default. (Stubben, Milligan and Nantel 2013, Caswell 2001 see section 12.1.5.2).</p><p>The goal of a demographic analysis is very often to estimate lambda, because lambda is estimated from imperfect data, such estimation are uncertain. Therefore, when the results have policy implications it is important to quantify that uncertainty. Confidence interval is one of the traditional tools to doing so (see outputs: Confidence interval of Lambda).</p><p>Analyses:</p><p>Lambda (λ)</p><p>Mean matrix</p><p>Variance matrix</p><p>Histogram</p><p>Confidence interval of Lambda</p><p>X= List of resampled matrices.</p>
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Maria Paula Balcazar-Vargas
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https://myexperiment.org/files/1237/download/Documentation_Parametric_Bootstrap_V3_update 2014-07-25.pdf
2014-07-25 09:41:10 UTC
by-sa
analysis
biovel
confidence interval of lambda
demography
gentiana pneumonanthe
histogram
lambda or dominant eigenvalue
matrix
matrix population models
mean matrix
model
package ‘popbio’ in r
population
stage matrix
population projection