simulation_master_list: simulation_master_list
In knnwtsim: K Nearest Neighbor Forecasting with a Tailored Similarity Metric
simulation_master_list R Documentation
simulation_master_list
Description
A list of 20 lists. Each of the 20 lists contains 31 items including 4 simulated time series.
Each series contains an ARIMA component, a periodic component simulated using trig functions, a component determined by a functional relationship
to exogenous predictors which we will call the f(x) component, a constant, and finally additional noise generated from either a
Gaussian distribution with mean = 0, or Poisson distribution. The 4 series within a given sublist only differ based on the f(x) component of the series. One series, series.mvnormx, uses
a matrix X generated by MASS::mvrnorm() with corresponding coefficients for the f(x) component. All other
series use piece-wise functional relationships for the f(x) component of the series.
Usage
simulation_master_list
Format
A list containing 20 sublists each with 31 items:
- series.len
the number of observations in the simulated time series
- random.seed
the random seed used in set.seed() for all random components in the sublist.
- arima.p
The AR order argument for stats::arima.sim().
- arima.d
The differencing order argument for stats::arima.sim().
- arima.q
The MA order argument for stats::arima.sim().
- ar.coefficients
Coefficients for the AR process in stats::arima.sim(),NULL if arima.p=0.
- ma.coefficients
Coefficients for the MA process in stats::arima.sim(),NULL if arima.q=0.
- seasonal.periods
The number of periods in a full cycle for the periodic component of the series.
- sin.coef
Coefficient on the sin term of the periodic component of the series.
- cos.coef
Coefficient on the cos term of the periodic component of the series.
- X.cols
Number of predictors used to generate the f(x) component of series.mvnormx.
- X.mu
The mean vector used in MASS::mvrnorm() to generate X for the f(x) component of series.mvnormx.
- X.Sigma
The covariance matrix generated by clusterGeneration::rcorrmatrix() used in MASS::mvrnorm() to generate X for the f(x) component of series.mvnormx.
- X
The matrix of X.cols predictors generated by MASS::mvrnorm() used to generate the f(x) component of series.mvnormx.
- x.coef
The vector of X.cols coefficients corresponding to the predictors of X used to generate the f(x) component of series.mvnormx.
- x.chng.mu
The mean value used in stats::rnorm() used to generate x.chng.
- x.chng.sd
The standard deviation value used in stats::rnorm() used to generate x.chng.
- x.chng.coef1
A coefficient for x.chng used in all piece-wise functional relationship, f(x), components, as the coef argument to lin.to.sqrt() and quad.to.cubic
and the coef1 argument to lin.coef.change .
- x.chng.coef2
A coefficient for x.chng used in the piece-wise functional relationship, f(x), component of series.lin.coef.chng.x, as the coef2 argument to lin.coef.change .
- x.chng.break.point
A value used in two piece-wise functional relationship, f(x), components, as the break.point argument to quad.to.cubic and lin.coef.change .
- x.chng.break.point.sqrt
The max() of x.chng.break.point and some value > 0. Used in the piece-wise functional relationship, f(x), component of series.lin.to.sqrt.x , as the break.point argument to lin.to.sqrt.
- x.chng
A vector of observations of a single predictor used to generate the f(x) component of all series other than series.mvnormx.
- type.noise
The family of probability distributions to to generate the additional noise component.
- poisson.rate
The lambda argument of stats::rpois() used to generate additional noise, only actually used if type.noise = 'poisson'.
- norma.sd
The sd argument of stats::rnorm() used to generate additional noise, only actually used if type.noise = 'normal'.
- constant
A numeric value which is the constant component of the series.
- series.mvnormx
A simulated time series generated from the sum of ARIMA, Periodic, f(x), noise, and constant components. In this case f(x) represents linear relationships to the columns of the matrix X.
- series.lin.to.sqrt.x
A simulated time series generated from the sum of ARIMA, Periodic, f(x), noise, and constant components. In this case f(x) represents a linear relationship to a single predictor x.chng which changes to a sqrt(x.chng)
relationship when x.chng > x.chng.break.point.sqrt.
- series.lin.coef.chng.x
A simulated time series generated from the sum of ARIMA, Periodic, f(x), noise, and constant components. In this case f(x) represents a linear relationship to a single predictor x.chng which changes coefficient when
x.chng > x.chng.break.point.
- series.quad.to.cubic.x
A simulated time series generated from the sum of ARIMA, Periodic, f(x), noise, and constant components. In this case f(x) represents a quadratic relationship to a single predictor x.chng which changes to a cubic relationship when
x.chng > x.chng.break.point, in addition a coefficient changes sign at x.chng.break.point.
Details
Below we have the functional relationships used for the piece-wise series:
lin.to.sqrt <- function(x, break.point, coef){
if (x < break.point) {
out <- coef * x
} else {
out <- sqrt(x)
}
return(out)
}
quad.to.cubic <- function(x, break.point, coef){
if (x < break.point) {
out <- coef * (x ** 2)
} else {
out <- -coef * (x ** 3)
}
return(out)
}
lin.coef.change <- function(x, break.point, coef1, coef2){
if (x < break.point) {
out <- coef1 * x
} else {
out <- coef2 * x
}
return(out)
}
Source
https://github.com/mtrupiano1/knnwtsim/blob/main/data-raw/simulation_master_list.R
knnwtsim documentation built on March 18, 2022, 6 p.m.
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| simulation_master_list | R Documentation |
simulation_master_list
Description
A list of 20 lists. Each of the 20 lists contains 31 items including 4 simulated time series.
Each series contains an ARIMA component, a periodic component simulated using trig functions, a component determined by a functional relationship
to exogenous predictors which we will call the f(x) component, a constant, and finally additional noise generated from either a
Gaussian distribution with mean = 0, or Poisson distribution. The 4 series within a given sublist only differ based on the f(x) component of the series. One series, series.mvnormx, uses
a matrix X generated by MASS::mvrnorm() with corresponding coefficients for the f(x) component. All other
series use piece-wise functional relationships for the f(x) component of the series.
Usage
simulation_master_list
Format
A list containing 20 sublists each with 31 items:
- series.len
the number of observations in the simulated time series
- random.seed
the random seed used in
set.seed()for all random components in the sublist.- arima.p
The AR order argument for
stats::arima.sim().- arima.d
The differencing order argument for
stats::arima.sim().- arima.q
The MA order argument for
stats::arima.sim().- ar.coefficients
Coefficients for the AR process in
stats::arima.sim(),NULLifarima.p=0.- ma.coefficients
Coefficients for the MA process in
stats::arima.sim(),NULLifarima.q=0.- seasonal.periods
The number of periods in a full cycle for the periodic component of the series.
- sin.coef
Coefficient on the sin term of the periodic component of the series.
- cos.coef
Coefficient on the cos term of the periodic component of the series.
- X.cols
Number of predictors used to generate the f(x) component of
series.mvnormx.- X.mu
The mean vector used in
MASS::mvrnorm()to generateXfor the f(x) component ofseries.mvnormx.- X.Sigma
The covariance matrix generated by
clusterGeneration::rcorrmatrix()used inMASS::mvrnorm()to generateXfor the f(x) component ofseries.mvnormx.- X
The matrix of
X.colspredictors generated byMASS::mvrnorm()used to generate the f(x) component ofseries.mvnormx.- x.coef
The vector of
X.colscoefficients corresponding to the predictors ofXused to generate the f(x) component ofseries.mvnormx.- x.chng.mu
The mean value used in
stats::rnorm()used to generatex.chng.- x.chng.sd
The standard deviation value used in
stats::rnorm()used to generatex.chng.- x.chng.coef1
A coefficient for
x.chngused in all piece-wise functional relationship, f(x), components, as thecoefargument tolin.to.sqrt()andquad.to.cubicand thecoef1argument tolin.coef.change.- x.chng.coef2
A coefficient for
x.chngused in the piece-wise functional relationship, f(x), component ofseries.lin.coef.chng.x, as thecoef2argument tolin.coef.change.- x.chng.break.point
A value used in two piece-wise functional relationship, f(x), components, as the
break.pointargument toquad.to.cubicandlin.coef.change.- x.chng.break.point.sqrt
The
max()ofx.chng.break.pointand some value > 0. Used in the piece-wise functional relationship, f(x), component ofseries.lin.to.sqrt.x, as thebreak.pointargument tolin.to.sqrt.- x.chng
A vector of observations of a single predictor used to generate the f(x) component of all series other than
series.mvnormx.- type.noise
The family of probability distributions to to generate the additional noise component.
- poisson.rate
The
lambdaargument ofstats::rpois()used to generate additional noise, only actually used iftype.noise = 'poisson'.- norma.sd
The
sdargument ofstats::rnorm()used to generate additional noise, only actually used iftype.noise = 'normal'.- constant
A numeric value which is the constant component of the series.
- series.mvnormx
A simulated time series generated from the sum of ARIMA, Periodic, f(x), noise, and constant components. In this case f(x) represents linear relationships to the columns of the matrix
X.- series.lin.to.sqrt.x
A simulated time series generated from the sum of ARIMA, Periodic, f(x), noise, and constant components. In this case f(x) represents a linear relationship to a single predictor
x.chngwhich changes to asqrt(x.chng)relationship whenx.chng > x.chng.break.point.sqrt.- series.lin.coef.chng.x
A simulated time series generated from the sum of ARIMA, Periodic, f(x), noise, and constant components. In this case f(x) represents a linear relationship to a single predictor
x.chngwhich changes coefficient whenx.chng > x.chng.break.point.- series.quad.to.cubic.x
A simulated time series generated from the sum of ARIMA, Periodic, f(x), noise, and constant components. In this case f(x) represents a quadratic relationship to a single predictor
x.chngwhich changes to a cubic relationship whenx.chng > x.chng.break.point, in addition a coefficient changes sign atx.chng.break.point.
Details
Below we have the functional relationships used for the piece-wise series:
lin.to.sqrt <- function(x, break.point, coef){
if (x < break.point) {
out <- coef * x
} else {
out <- sqrt(x)
}
return(out)
}
quad.to.cubic <- function(x, break.point, coef){
if (x < break.point) {
out <- coef * (x ** 2)
} else {
out <- -coef * (x ** 3)
}
return(out)
}
lin.coef.change <- function(x, break.point, coef1, coef2){
if (x < break.point) {
out <- coef1 * x
} else {
out <- coef2 * x
}
return(out)
}
Source
https://github.com/mtrupiano1/knnwtsim/blob/main/data-raw/simulation_master_list.R
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