Estimates a single variate MIDAS model.
midas_estimate(
est.y,
est.x,
est.lag.y,
est.xdate,
polynomial,
loss,
num.evals,
num.coef,
startx_all = NULL,
seed = NULL,
...
)response variable.
predictor variable lags in MIDAS data format.
autoregressive lags of response variable (if NULL DL-MIDAS model is estimated).
predictor variable lag dates in MIDAS data format.
MIDAS lag polynomial specification.
loss function.
number of objective function evaluations using random starting parameter values.
number of best coefficients to use as starting values in nonlinear optimization.
starting values to feed into optimization algorithm.
value used in set.seed for randomly drawing initial starting values.
optional parameters to feed into other functions.
returns estimates of coefficient vector for a desired model specification.
For specficiation details, midas_dl or midas_ardl function descriptions for more details.