cfda-package |
Categorical Functional Data Analysis |
biofam2 |
Family life states from the Swiss Household Panel biographical survey |
boxplot.timeSpent |
Boxplot of time spent in each state |
care |
Care trajectories |
compute_duration |
Compute duration of individuals |
compute_number_jumps |
Compute the number of jumps |
compute_optimal_encoding |
Compute the optimal encoding for each state |
compute_time_spent |
Compute time spent in each state |
convertToCfd |
Convert data to categorical functional data |
cut_data |
Cut data to a maximal given time |
estimate_Markov |
Estimate transition matrix and spent time |
estimate_pt |
Estimate probabilities to be in each state |
flours |
Flours dataset |
generate_2State |
Generate data following a 2 states model |
generate_Markov |
Generate Markov Trajectories |
get_encoding |
Extract the computed encoding |
get_state |
Extract the state of each individual at a given time |
hist.duration |
Plot the duration |
hist.njump |
Plot the number of jumps |
matrixToCfd |
Convert a matrix to a cfda data.frame |
plot.fmca |
Plot the optimal encoding |
plot.Markov |
Plot the transition graph |
plot.pt |
Plot probabilities |
plotComponent |
Plot Components |
plotData |
Plot categorical functional data |
plotEigenvalues |
Plot Eigenvalues |
predict.fmca |
Predict the principal components for new trajectories |
print.fmca |
Print a 'fmca' object |
remove_duplicated_states |
Remove duplicated states |
statetable |
Table of transitions |
summary.fmca |
Object Summaries |
summary_cfd |
Summary |