This function creates an object of class RprobitB_parameter
, which
contains the parameters of a probit model.
If sample = TRUE
, missing parameters are sampled. All parameters are
checked against the values of P_f
, P_r
, J
, and N
.
Note that parameters are automatically ordered with respect to a
non-ascending s
for class identifiability.
Usage
RprobitB_parameter(
P_f,
P_r,
J,
N,
C = 1,
ordered = FALSE,
alpha = NULL,
s = NULL,
b = NULL,
Omega = NULL,
Sigma = NULL,
Sigma_full = NULL,
beta = NULL,
z = NULL,
d = NULL,
sample = TRUE
)
# S3 method for class 'RprobitB_parameter'
print(x, ..., digits = 4)
Arguments
- P_f
[
integer(1)
]
The number of covariates connected to a fixed coefficient.- P_r
[
integer(2)
]
The number of covariates connected to a random coefficient.- J
[
integer(1)
]
The number >= 2 of choice alternatives.- N
[
integer(1)
]
The number of decision makers.- C
[
integer(1)
]
The number (greater or equal 1) of latent classes of decision makers.- ordered
[
logical(1)
]
IfTRUE
, the choice setalternatives
is assumed to be ordered from worst to best.- alpha
[
numeric(P_f)
]
The fixed coefficient vector.- s
[
numeric(C)
]
The vector of class weights.- b
[
matrix(nrow = P_r, ncol = C)
]
The matrix of class means as columns.- Omega
[
matrix(nrow = P_r * P_r, ncol = C)
]
The matrix of vectorized class covariance matrices as columns.- Sigma
[
matrix(nrow = J - 1, ncol = J - 1)
|numeric(1)
]
The differenced (wrt. alternativeJ
) error covariance matrix.In case of
ordered = TRUE
, the single error variance.- Sigma_full
[
matrix(nrow = J, ncol = J)
]
The error covariance matrix.Ignored if
Sigma
is specified orordered = TRUE
.Internally,
Sigma_full
gets differenced wrt. alternativeJ
.- beta
[
matrix(nrow = P_r, ncol = N)
]
The matrix of the decider-specific coefficient vectors.- z
[
numeric(N)
]
The decider class allocations.- d
[
numeric(J - 2)
]
The logarithmic increases of the utility thresholds in the ordered probit case (ordered = TRUE
).- sample
[
logical(1)
]
Sample missing parameters?- x
An
RprobitB_parameter
object.- ...
[
character()
]
Names of parameters to be printed. If not specified, all parameters are printed.- digits
[
integer(1)
]
The number of decimal places.
Examples
RprobitB_parameter(P_f = 1, P_r = 2, J = 3, N = 10, C = 2)
#> alpha : -0.9
#>
#> C : 2
#>
#> s : double vector of length 2
#> 0.76 0.24
#>
#> b : 2 x 2 matrix of doubles
#> [,1] [,2]
#> [1,] -0.8 1.3
#> [2,] 3.0 -2.5
#>
#>
#> Omega : 4 x 2 matrix of doubles
#> [,1] [,2]
#> [1,] 1.15 1.26
#> [2,] 0.06 -0.21
#> [3,] 0.06 -0.21
#> [4,] 1.2 1.98
#>
#>
#> Sigma : 2 x 2 matrix of doubles
#> [,1] [,2]
#> [1,] 2.80 1.42
#> [2,] 1.42 2.36
#>
#>
#> Sigma_full : 3 x 3 matrix of doubles
#> [,1] [,2] [,3]
#> [1,] 1.77 0.36 0.06
#> [2,] 0.36 1.27 0.03
#> [3,] 0.06 0.03 1.14
#>
#>
#> beta : 2 x 10 matrix of doubles
#> [,1] [,2] [,3] ... [,10]
#> [1,] 1.56 0.01 0.06 ... 2.68
#> [2,] -3.14 -3.16 1.98 ... -2.9
#>
#>
#> z : double vector of length 10
#> 2 2 1 ... 2
#>
#> d : NA
#>