- data
The dataframe containing the survey data
- marginMatrix
The matrix giving the margins for each column variable included
in the calibration problem
- colWeights
The name of the column containing the initial weights in the survey
dataframe
- method
The method used to calibrate. Can be "linear", "raking", "logit"
- bounds
Two-element vector containing the lower and upper bounds for bounded methods
("logit")
- q
Vector of q_k weights described in Deville and Sarndal (1992)
- costs
The penalized calibration method will be used, using costs defined by this
vector. Must match the number of rows of marginMatrix. Negative of non-finite costs are given
an infinite cost (coefficient of C^-1 matrix is 0)
- gap
Only useful for penalized calibration. Sets the maximum gap between max and min
calibrated weights / initial weights ratio (and thus is similar to the "bounds"
parameter used in regular calibration)
- popTotal
Precise the total population if margins are defined by relative value in
marginMatrix (percentages)
- pct
If TRUE, margins for categorical variables are considered to
be entered as percentages. popTotal must then be set. (FALSE by default)
- scale
If TRUE, stats (including bounds) on ratio calibrated weights / initial weights are
done on a vector multiplied by the weighted non-response ratio (ratio population total /
total of initial weights). Has same behavior as "ECHELLE=0" in Calmar.
- description
If TRUE, output stats about the calibration process as well as the
graph of the density of the ratio calibrated weights / initial weights
- maxIter
The maximum number of iterations before stopping
- check
performs a few check about the dataframe. TRUE by default
- calibTolerance
Tolerance for the distance to an exact solution.
Could be useful when there is a huge number of margins as the risk of
inadvertently setting incompatible constraints is higher. Set to 1e-06 by default.
- uCostPenalized
Unary cost by which every cost is "costs" column is multiplied
- lambda
The initial ridge lambda used in penalized calibration. By default, the initial
lambda is automatically chosen by the algorithm, but you can speed up the search for the optimum
if you already know a lambda close to the lambda_opt corresponding to the gap you set. Be careful,
the search zone is reduced when a lambda is set by the user, so the program may not converge
if the lambda set is too far from the lambda_opt.
- precisionBounds
Only used for calibration on minimum bounds. Desired precision
for lower and upper reweighting factor, both bounds being as close to 1 as possible
- forceSimplex
Only used for calibration on tight bounds.Bisection algorithm is used
for matrices whose size exceed 1e8. forceSimplex = TRUE forces the use of the simplex algorithm
whatever the size of the problem (you might want to set this parameter to TRUE if you
have a large memory size)
- forceBisection
Only used for calibration on tight bounds. Forces the use of the bisection
algorithm to solve calibration on tight bounds
- colCalibratedWeights
Deprecated. Only used in the scope of calibration function
- exportDistributionImage
File name to which the density plot shown when
description is TRUE is exported. Requires package "ggplot2"
- exportDistributionTable
File name to which the distribution table of before/after
weights shown when description is TRUE is exported. Requires package "xtable"