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Documentation_Parametric_Bootstrap_V3_update 2014-07-25.pdf
2014-07-25T09:41:10Z
2014-07-25T09:41:10Z
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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9e25ddadf8aea9e360cf2c82bc1a5ce411c7061b
Academy
Matrix population models and Integral projection models
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2009-05-21T10:32:59Z
2010-04-23T12:56:44Z
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2009-07-08T14:09:36Z
2009-07-08T14:09:37Z
Documentation_Parametric_Bootstrap_V3_update 2014-07-25.pdf
2014-07-25T09:41:10Z
2014-07-25T09:41:10Z
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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