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 |