This menu choice loads Excel worksheets that demonstrate the use of PopTools.
Demo sheet |
Explanation |
Analysis of a projection matrix | Calculation of rate of increase, age structure, reproductive value and generation times |
Randomisation test (two sample) | How to conduct a simple randomisation test |
Randomisation test (distance matrix) | How to conduct a randomisation test on distance matrices (Mantel test) |
Correlated variables | How to generate a sequence of correlated random variables |
Covariance matrix | Some different ways to compute a variance-covariance matrix for a data matrix of species abundance within plots |
Gtest | Calculation of G - statistic |
Jolly | Jolly-Seber estimate of abundance in quadrats or transects |
Likelihood | Some simple likelihoods |
Jackknife | How to compute Jackknife statistics in Excel |
Mantel test | How to use the MANTEL worksheet function |
Matrix decompositions | Demo of matrix decompositions - LU, QR, SVD, Cholesky |
Matrix projection | Different ways to project with matrices |
Numerical projection | Simulation of a discrete time process (deterministic) |
Numerical projection (stochastic) | Simulation of a discrete time process (stochastic) |
PBLR test | Calculation of the parametric bootstrap likelihood ratio (PBLR) test for density-dependence in a time series |
PCADemo | Calculation of a principal components analysis |
Pollard's test | Calculation of the test of Pollard, E., Lakhani, K. H. & Rothery, P. (1987) for density-dependence in a time series |
Random variables (general) | Generation of random variables using PopTools |
Random variables (fast) | More information on generation of random variables using PopTools |
Resampling | More information on the routines for shuffling and resampling from data matrices |
Sensitivity-Elasticity | Numerical sensitivity analysis of "any" model. Sensitivity and elasticity for matrix models |
Singular value decomp | Demo of singular value decomposition |