fix.fit {SIMle} | R Documentation |
User-specified estimation of nonlinear time series regression
Description
This function estimates nonlinear time series regression by sieve methods
Usage
fix.fit(
ts,
c,
d,
b_time,
b_timese,
mp_type,
type,
fix_num = 0,
r = 1,
s = 1,
n_esti = 2000,
upper = 10
)
Arguments
ts |
ts is the data set which is a time series data typically |
c |
number of basis for time input |
d |
number of basis for variate input |
b_time |
type of basis for time input |
b_timese |
type of basis for variate input |
mp_type |
select type of mapping function, "algeb" indicates algebraic mapping on the real line. "logari" represents logarithmic mapping on the real line |
type |
select type of estimation."nfix" refers to no fix estimation. "fixt" indicates fix time t estimation. "fixx" represents fix variate estimation |
fix_num |
fix_num indicates the use of fixed-value nonlinear time series regression. The default value is 0, which is employed for non-fixed estimation. If "fixt" is chosen, it represents a fixed time value. Otherwise, if not selected, it pertains to a fixed variate value |
r |
indicates number of variate |
s |
s is a positive scaling factor, the default is 1 |
n_esti |
number of points for estimation, the default is 2000 |
upper |
upper The upper bound for the variate basis domain. The default value is 10. When "algeb" or "logari" is chosen, the domain is automatically set from -upper to upper |
Value
If "nfix" is selected, the function returns a list where each element is a matrix representing the estimation function in two dimensions. Otherwise, if "nfix" is not selected, the function returns a list where each element is a vector representing the estimation function.