GeneratePanel {CluMP} | R Documentation |

## Generate an artificial Micro-Panel (longitudinal) Data

### Description

This function creates artificial linear or non-linear micro-panel (longitudinal) data coming from generating process with a certain function (linear, quadratic, cubic, exponencial) set of parameters (fixed and random (intercept, slope) effects of time).

### Usage

```
GeneratePanel(
n,
Param,
NbVisit,
VisitFreq = NULL,
TimeVar = NULL,
RegModel = NULL,
ClusterProb = NULL,
Rho = NULL,
units = NULL
)
```

### Arguments

`n` |
An integer specifying the number of individuals (trajectories) being observed. |

`Param` |
Object of |

`NbVisit` |
A positive integer numeric input defining expected number of visits. Option is |

`VisitFreq` |
String that defines the frequency of visits for each individual. Option is |

`TimeVar` |
A positive integer representing daily, time variability of the occurrence of repeated measurement (timepoint) from the regular, fixed occurrence (visit) given by the argument units. For example, if this argument is set to 5 then the random integer from interval of -5 to 5 is drawn and added to the time variable. TimeVar must be lower than the regular frequency of repeat measurement given by the argument units. |

`RegModel` |
String specifying the mathematical function for generating trajectory for each of n individuals. Options are |

`ClusterProb` |
Numeric scalar (for 2 clusters) or a vector of numbers (for >2 clusters) defining the probability of each cluster. If not defined, then each cluster has the same occurrence probability. |

`Rho` |
A numeric scalar specifying autocorrelation parameter with the values from range 0 to 1. If set as 0 or not define then there is no autocorrelation between the within-individual repeated observations. |

`units` |
String defining the units of time series. Options are |

### Value

Generates artificial panel data.

### Examples

```
set.seed(123)
#Simple Linear model where each individual has 10 observations.
data <- GeneratePanel(n = 100, Param = ParamLinear, NbVisit = 10)
#Exponential model where each individual has 10 observations.
data <- GeneratePanel(100, ParamExpon, NbVisit = 10, VisitFreq = "Fixed", RegModel = "exponential")
PanelPlot(data)
#Cubic model where each individual has random number of observations on daily basis.
#Average number of observation is given by parameter NbVisit.
data <- GeneratePanel(n = 100, Param = ParamCubic, NbVisit = 100, RegModel = "cubic", units = "day")
PanelPlot(data)
#Quadratic model where each individual has random number of observations.
#Each object is observede weekly with variability 2 days.
data <- GeneratePanel(5,ParamQuadrat,NbVisit=50,RegModel="quadratic",units="week",TimeVar=2)
PanelPlot(data)
#Generate panel data with linear trend with 75% objects in first cluster and 25% in the second.
data <- GeneratePanel(n = 100, Param = ParamLinear, NbVisit = 10, ClusterProb = c(0.75, 0.25))
PanelPlot(data, colour = "Cluster")
```

*CluMP*version 0.8.1 Index]