Description Usage Arguments Value Author(s) Examples

View source: R/march.dataset.R

The function creates a `march.Dataset-class`

from a *dataframe* or a *matrix*, where each row (resp. column) represents
an independent data series when *MARGIN* is 2 (resp. 1).

1 2 3 4 5 6 7 | ```
march.dataset.loadFromDataFrame(
dataframe,
MARGIN = 2,
weights = NA,
missingDataRep = NA,
covariates = NULL
)
``` |

`dataframe` |
A |

`MARGIN` |
The dimension of the matrix/data.frame that contains the sequences and of the covariates (resp 1 for the column, 2 for the rows). |

`weights` |
If specified, contains the weight of each sequence. |

`missingDataRep` |
If specified, the symbol representing a missing data. |

`covariates` |
If specified, a three dimensional array of integers, representing the covariates. The data for the i-th covariates should be in [, , i]. If the data are column-wise (respectively row-wise), each table of covariates should be column-wise (respectively row-wise). If we only have one covariate, we can simply pass a two-dimensional array. The covariates should be coded as integers from 1 to the number of possible outputs. |

A `march.Dataset-class`

object containing the data contructed from the matrix or data.frame.

Ogier Maitre

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | ```
# Create a march dataset from the sleep_df dataframe included in the march package.
sleep <- march.dataset.loadFromDataFrame(sleep_df, MARGIN = 2,
weights = NA, missingDataRep = NA)
# Each row of sleep_df contains the data for one subject, so MARGIN was set to 2.
# Most of the subjects have been observed during 7 consecutive years,
# but some subjects have been observed for only 5 or 6 years.
# To load only the first 5 observations of each subject:
sleep.5 <- march.dataset.loadFromDataFrame(sleep_df[,1:5], MARGIN = 2 ,
weights = NA, missingDataRep = NA)
# The sleep data are not weighted.
# To add a weighting variable taking value 1.5 for the 500 first subjects
# and value 0.5 for the 500 next:
weighting <- rep(1.5,1000)
weighting[501:1000] <- rep(0.5,500)
sleep.w <- march.dataset.loadFromDataFrame(sleep_df, MARGIN = 2,
weights = weighting, missingDataRep = NA)
# We add two covariates to the sleep data. The first is the sex of the subject
# (1 for male, 2 for female), and the second is the age range (1 for younger
# than 40, 2 for older than 40). We suppose that the first 250 sequences
# represent men older than 40, the next 250 sequences men younger than 40,
# the next 250 women younger than 40 and the last 250 women older than 40.
# We build the two tables of covariates and bind them together to obtain a
# three dimensional array that can be handled by MARCH.
covariates.sex<-rbind(matrix(1,500,7),matrix(1,500,7))
covariates.age<-rbind(matrix(1,250,7), matrix(2,250,7), matrix(1,250,7),
matrix(2,250,7))
covariates<-array(0,c(1000,7,2))
covariates[ , ,1]<-covariates.sex
covariates[ , ,2]<-covariates.age
# We build a MARCH dataset object containing these covariates.
sleep.covariates<-march.dataset.loadFromDataFrame(sleep_df,covariates=covariates)
``` |

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