error_lphom {lphom}

Global error of a lphom estimated table

Description

Estimation of the error index (EI) of a RxC vote transfer matrix obtained with lphom()

Usage

error_lphom(
  lphom.object,
  upper.alfa = 0.1,
  show.plot = TRUE,
  num.d = 11,
  B = 30
)

Arguments

lphom.object

An object output of the lphom() function.

upper.alfa

Upper bound that will not be exceed by the EI estimate with a confidence 1 - alpha. By default, 0.10.

show.plot

TRUE/FALSE. Indicates whether the plot showing the relationship between EI and HETe estimated by simulation for the election under study should be displayed as a side-effect. By default, TRUE.

num.d

Number maximum of different disturbances, d, to be initially considered. Positive integer greater than or equal to 5. By default, 11.

B

Integer that determines the number of simulations to be performed for each disturbance value. By default, 30.

Value

A list with the following components

EI.estimate

Point estimate for EI.

EI.upper

Upper bound with confidence 1 - alpha of the EI estimate

figure

ggplot2 object describing the graphical representation of the relationship between EI and HETe.

equation

lm object of the adjustment between EI and HETe.

statistics

A four column matrix with the values of HET, HETe, EI and d associated with each simulated scenario.

TMs.real

Array with the simulated real transfer matrices associated with each scenario.

TMs.estimate

Array with the estimated transfer matrices associated with each scenario.

Note

ggplot2 is needed to be installed for this function to work.

See equation (12) in Romero et al. (2020) for a definition of the EI index.

Author(s)

Jose M. Pavia, [e-mail]

Rafael Romero [e-mail]

References

Romero, R, Pavia, JM, Martin, J and Romero G (2020). Assessing uncertainty of voter transitions estimated from aggregated data. Application to the 2017 French presidential election. Journal of Applied Statistics, 47(13-15), 2711-2736. doi:10.1080/02664763.2020.1804842

See Also

lphom confidence_intervals_pjk

Examples

mt.lphom <- lphom(France2017P[, 1:8], France2017P[, 9:12], 
                  new_and_exit_voters = "raw", verbose = FALSE)
set.seed(253443)
example <- error_lphom(mt.lphom, upper.alfa = 0.10, show.plot = FALSE, num.d = 5, B = 8)
example$EI.estimate