R: Changepoint Detection via Modified Genetic Algorithms

# Changepoint Detection via Modified Genetic Algorithms

## Documentation for package ‘changepointGA’ version 0.1.5

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

amoc_crossover | Average crossover operator to produce offspring for AMOC problem
amoc_mutation | Jump mutation operator to produce offspring for AMOC problem
amoc_population | Random population initialization for AMOC problem
amoc_selection | The parents selection genetic algorithm operator for AMOC problem
arima_bic | Example function: Calculating BIC for AR(1) model
arima_bic_order_pq | Calculating BIC for Multiple changepoint detection with AR and MA order selection
cptga | Genetic algorithm
cptga-class | S4 Class Definition for 'cptga'
cptgaisl | Island model based genetic algorithm
cptgaisl-class | S4 Class Definition for 'cptgaisl'
cpt_dist | Comparing multiple changepoint configurations by pairwise distance
mutation | The default mutation operator in genetic algorithm
plot.cptga | Plot Time Series with Detected Changepoints from a 'cptga' Object
plot.cptgaisl | Plot Time Series with Detected Changepoints from a 'cptgaisl' Object
print.summary.cptga | Print Summary for a 'cptga' Object
print.summary.cptgaisl | Print Summary for a 'cptgaisl' Object
random_population | Random population initialization
selection_linear_rank | The default parents selection genetic algorithm operator
select_tau | Randomly select the chromosome
summary-method | S4 Class Definition for 'cptga'
summary-method | S4 Class Definition for 'cptgaisl'
summary.cptga | S4 Class Definition for 'cptga'
summary.cptgaisl | S4 Class Definition for 'cptgaisl'
ts_sim | Time series simulation with changepoint effects
uniform_crossover | Uniform crossover to produce offsprings