Description Usage Arguments Details Value References See Also Examples
View source: R/variance_othstr.R
Computes s2g and the variance estimation by the new stratification.
1 2 3 4 5 6 7 8 9 10 11 | variance_othstr(
Y,
H,
H2,
w_final,
N_h = NULL,
N_h2,
period = NULL,
dataset = NULL,
checking = TRUE
)
|
Y |
Variables of interest. Object convertible to |
H |
The unit stratum variable. One dimensional object convertible to one-column |
H2 |
The unit new stratum variable. One dimensional object convertible to one-column |
w_final |
Weight variable. One dimensional object convertible to one-column |
N_h |
optional; either a |
N_h2 |
optional; either a |
period |
Optional variable for the survey periods. If supplied, the values for each period are computed independently. One dimensional object convertible to one-column |
dataset |
Optional survey data object convertible to |
checking |
Optional variable if this variable is TRUE, then function checks data preparation errors, otherwise not checked. This variable by default is TRUE. |
It is possible to compute population size M_g from sampling frame. The standard deviation of g-th stratum is
S_g^2 =1/(M_g-1) ∑ k=1...M_g (y_gk - Ym_g)^2= 1/(M_g-1) ∑ k=1...M_g (y_gk)^2 - M_g/(M_g-1)*(Ym_g)^2
∑ k=1...M_g (y_gk)^2 and Ym_g^2 have to be estimated to estimate S_g^2. Estimate of ∑ k=1...M_g (y_gk)^2 is ∑ h=1...H N_h/n_h ∑ i=1...n_h (y_gi)^2*z_hi, where
z_hi=if(0, h_i notin θ_g; 1, h_i in θ_g) , θ_g is the index group of successfully surveyed units belonging to g-th stratum. #'Estimate of (Y_g)^2 is
Ym_g^2=(Ym_g)^2- Var(Ym)
Ym_g =Ym_g/M_g= 1/M_g ∑ h=1...H N_h/n_h ∑ i=1...n_h y_hi z_hi
So the estimate of S_g^2 is
s_g^2=\1/(M_g-1) ∑ h=1...H N_h/n_h ∑ i=1...n_h (y_hi)^2 * z_hi -
-M_g/(M_g-1) (1/M_g ∑ h=1...H N_h/n_h ∑ i=1...n_h y_hi z_hi)^2
Two conditions have to realize to estimate S_g^2: n_h>1, forall g and θ_g <> 0, forall g.
Variance of Y is
Var(Y) = ∑ g=1...G M_g^2 (1/m_g - 1/M_g)*(S_g)^2
Estimate of Var(Y) is
Var(Y)= ∑ g=1...G M_g^2 (1/m_g - 1/M_g)*(s_g)^2
A list with objects are returned by the function:
betas A numeric data.table
containing the estimated coefficients of calibration.
s2g A data.table
containing the s^2g value.
var_est A data.table
containing the values of the variance estimation.
M. Liberts. (2004) Non-response Analysis and Bias Estimation in a Survey on Transportation of Goods by Road.
domain
, lin.ratio
, linarpr
,
linarpt
, lingini
, lingini2
,
lingpg
, linpoormed
, linqsr
,
linrmpg
, residual_est
, vardom
,
vardom_othstr
, vardomh
, varpoord
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | library("data.table")
Y <- data.table(matrix(runif(50) * 5, ncol = 5))
H <- data.table(H = as.integer(trunc(5 * runif(10))))
H2 <- data.table(H2 = as.integer(trunc(3 * runif(10))))
N_h <- data.table(matrix(0 : 4, 5, 1))
setnames(N_h, names(N_h), "H")
N_h[, sk:= 10]
N_h2 <- data.table(matrix(0 : 2, 3, 1))
setnames(N_h2, names(N_h2), "H2")
N_h2[, sk2:= 4]
w_final <- rep(2, 10)
vo <- variance_othstr(Y = Y, H = H, H2 = H2,
w_final = w_final,
N_h = N_h, N_h2 = N_h2,
period = NULL,
dataset = NULL)
vo
|
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