# Demos

**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)

**Bootstrap**: How to bootstrap confidence limits

**Bias corrected percentiles**: How to calculate bias corrected percentile confidence limits

**Correlated variables**: How to generate a sequence of correlated random variables

**Distance matrix**: Calculate a distance matrix

**Eigenvector test**: Test routines to return eigenvalues/vectors

**Fit parameters**: Fit parameters by maximum likelihood

**fit distributions**: Find best fitting distribution

**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

**Jackknife**: How to compute Jackknife statistics in Excel

**Jolly**: Jolly-Seber estimate of abundance in quadrats or transects

**Life table**: Analysis of life tables using PopTools

**Likelihood**: Likelihoods for various error structures

**Likelihood profile**: Calculation of a likelihood profile

**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

**Monte Carlo**: Basic use of the Monte-Carlo routine

**Numerical projection**: Simulation of a discrete time process (deterministic)

**Numerical projection (stochastic)**: Simulation of a discrete time process (stochastic)

**ODE integration**: How to use the ODEIntegrate function to integrate a system of ordinary differential equations

**PBLR test**: Calculation of the parametric bootstrap likelihood ratio (PBLR) test for density-dependence in a time series

**PPS sample**: Selection of a sample with probability proportional to size

**Ordination**: Ordination using principal components analysis and correspondence analysis. General ordination using matrix algebra.

**Pollardâ€™s test**: Calculation of the test of Pollard, E., Lakhani, K. H. & Rothery, P. (1987) for density-dependence in a time series

**Power analysis**: How to do a power analysis by simulation

**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

**Risk analysis**: Quantitative risk analysis

**Sensitivity-Elasticity**: Numerical sensitivity analysis of deterministic models. Sensitivity and elasticity for matrix models

**Sensitivity (stochastic)**: Numerical sensitivity analysis of stochastic models

**Singular value decomp**: Demo of singular value decomposition

**Solve linear system**: Solve linear system using SVD/QR. MatInv function