disaggregate {TSdisaggregation} | R Documentation |
Temporal Disaggregation Methods
Description
This function contains the traditional standard-dimensional temporal disaggregation methods proposed by Denton (1971), Dagum and Cholette (2006), Chow and Lin (1971), Fernandez (1981) and Litterman (1983), and the high-dimensional methods of Mosley et al. (2021).
Usage
disaggregate(
Y,
X = matrix(data = rep(1, times = nrow(Y)), nrow = nrow(Y)),
aggMat = "sum",
aggRatio = 4,
method = "Chow-Lin",
Denton = "first"
)
Arguments
Y |
The low-frequency response series (n_l x 1 matrix). |
X |
The high-frequency indicator series (n x p matrix). |
aggMat |
Aggregation matrix according to 'first', 'sum', 'average', 'last' (default is 'sum'). |
aggRatio |
Aggregation ratio e.g. 4 for annual-to-quarterly, 3 for quarterly-to-monthly (default is 4). |
method |
Disaggregation method using 'Denton', 'Denton-Cholette', 'Chow-Lin', 'Fernandez', 'Litterman', 'spTD' or 'adaptive-spTD' (default is 'Chow-Lin'). |
Denton |
Type of differencing for Denton method: 'absolute', 'first', 'second' and 'proportional' (default is 'first'). |
Details
Takes in a n_l x 1 low-frequency series to be disaggregated Y and a n x p high-frequency matrix of p indicator series X. If n > n_l x aggRatio where aggRatio is the aggregation ration (e.g. aggRatio = 4 if annual-to-quarterly disagg or aggRatio = 3 if quarterly-to-monthly disagg) then extrapolation is done to extrapolate up to n.
Value
y_Est Estimated high-frequency response series (n x 1 matrix).
beta_Est Estimated coefficient vector (p x 1 matrix).
rho_Est Estimated residual AR(1) autocorrelation parameter.
ul_Est Estimated aggregate residual series (n_l x 1 matrix).
References
Chow GC, Lin A (1971).
“Best linear unbiased interpolation, distribution, and extrapolation of time series by related series.”
The review of Economics and Statistics, 372–375.
Dagum EB, Cholette PA (2006).
Benchmarking, temporal distribution, and reconciliation methods for time series, volume 186.
Springer Science \& Business Media.
Denton FT (1971).
“Adjustment of monthly or quarterly series to annual totals: an approach based on quadratic minimization.”
Journal of the american statistical association, 66(333), 99–102.
Fernandez RB (1981).
“A methodological note on the estimation of time series.”
The Review of Economics and Statistics, 63(3), 471–476.
Litterman RB (1983).
“A random walk, Markov model for the distribution of time series.”
Journal of Business \& Economic Statistics, 1(2), 169–173.
Mosley L, Eckley I, Gibberd A (2021).
“Sparse Temporal Disaggregation.”
arXiv preprint arXiv:2108.05783.
Examples
data = TempDisaggDGP(n_l=25,n=100,p=10,rho=0.5)
X = data$X_Gen
Y = data$Y_Gen
fit_chowlin = disaggregate(Y=Y,X=X,method='Chow-Lin')
y_hat = fit_chowlin$y_Est