Man pages for cfda
Categorical Functional Data Analysis
| biofam2 | Family life states from the Swiss Household Panel... |
| boxplot.timeSpent | Boxplot of time spent in each state |
| care | Care trajectories |
| cfda-package | Categorical Functional Data Analysis |
| 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 |
| plotComponent | Plot Components |
| plotData | Plot categorical functional data |
| plotEigenvalues | Plot Eigenvalues |
| plot.fmca | Plot the optimal encoding |
| plotIndicatorsReconstruction | Plot reconstructed indicators |
| plot.Markov | Plot the transition graph |
| plot.pt | Plot probabilities |
| predict.fmca | Predict the principal components for new trajectories |
| print.fmca | Print a 'fmca' object |
| reconstructIndicators | Reconstruct the indicators using encoding |
| remove_duplicated_states | Remove duplicated states |
| statetable | Table of transitions |
| summary_cfd | Summary |
| summary.fmca | Object Summaries |
