| Type: | Package |
| Title: | The Distributed Local PCA Algorithm |
| Version: | 0.0.5 |
| Date: | 2022-08-07 |
| Maintainer: | Guangbao Guo <ggb11111111@163.com> |
| Description: | Algorithm to handle with optimal subset selection for distributed local principal component analysis. The philosophy of the package is described in Guo G. (2020) <doi:10.1080/02331888.2020.1823979>. |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| Packaged: | 2022-08-07 00:54:18 UTC; 14482 |
| Author: | Guangbao Guo |
| Depends: | R (≥ 3.5.0) |
| RoxygenNote: | 7.2.0 |
| Suggests: | testthat (≥ 3.0.0) |
| Config/testthat/edition: | 3 |
| Repository: | CRAN |
| Date/Publication: | 2022-08-07 02:20:02 UTC |
Application
Description
Application data set
Usage
data("Application")
Format
The format is: int [1:48, 1:15] 6 9 7 5 6 7 9 9 9 4 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr [1:15] "FL" "APP" "AA" "LA" ...
Details
It is the scoring of 15 indicators on 48 interviewees
Examples
data(Application)
## maybe str(Application) ; plot(Application) ...
Distributed local PCA
Description
Calculate the estimator on the DLPCA method
Usage
DLPCA(X = X, n = n, p = p, m = m, K = K, L = L)
Arguments
X |
is the original data matrix |
n |
is the sample size |
p |
is the number of variables |
m |
is the number of eigenvalues |
K |
is the number of nodes |
L |
is the number of subgroups |
Value
time |
is the time cost |
V |
is the right singular matrix |
Vm |
is the m-right singular matrix |
Smean |
is the mean covariance matrix |
MMSER |
is the mean MSE values of the robust covariance matrix sub-estimators |
MMSES |
is the mean MSE values of the covariance matrix sub-estimators |
MMSEX |
is the mean MSE values of the sub-estimators of the matrix X |
MSER |
is the min MSE values of the robust covariance matrix sub-estimators |
MSES |
is the min MSE values of the covariance matrix sub-estimators |
MSEX |
is the min MSE values of the sub-estimators of the matrix X |
wMSER |
is the location of the min MSE values of the robust covariance matrix sub-estimators |
wMSES |
is the location of the min MSE values of the covariance matrix sub-estimators |
wMSEX |
is the location of the min MSE values of the sub-estimators of the matrix X |
sigm |
is the estimator of the covariance matrix of the matrix X |
Examples
data(Application)
X=Application
n=nrow(Application);p=ncol(Application)
m=5;L=4;K=4
DLPCA_result=DLPCA(X=X,n=n,p=p,m=m,K=K,L=L)
Iris
Description
Iris data set
Usage
data("Iris")
Format
A data frame with 150 observations on the following 5 variables.
Sepal.lengtha numeric vector
Sepal.widtha numeric vector
Petal.lengtha numeric vector
Petal.widtha numeric vector
Speciesa character vector
Details
It contains 150 samples with 5 variables
Source
Gaspar peninsula in Canada
Examples
data(Iris)
## maybe str(Iris) ; plot(Iris) ...
MSE on PCA
Description
Caculate the MSE value on PCA
Usage
MSEpca(V = V, X = X, n = n, p = p, m = m, K = K, L = L)
Arguments
V |
is the right singular matrix |
X |
is the orignal data set |
n |
is the sample size |
p |
is the number of variables |
m |
is the number of eigenvalues |
K |
is the number of nodes |
L |
is the number of subgroups |
Value
MSEpca |
the MSE value on PCA |
Examples
data(Application)
X=Application
n=nrow(Application);p=ncol(Application)
m=5;L=4;K=4
DLPCA_result=DLPCA(X=X,n=n,p=p,m=m,K=K,L=L)
V=DLPCA_result$V
MSEpca_result=MSEpca(V=V,X=X,n=n,p=p,m=m,K=K,L=L)
MSE_PCA=MSEpca_result$MSEpca
Gas-Turbine CO and NOx Emission Data
Description
Gas-Turbine CO and NOx Emission Data in 2011
Usage
data("gt2011")
Format
A data frame with 7411 observations on the following 11 variables.
ATa numeric vector
APa numeric vector
AHa numeric vector
AFDPa numeric vector
GTEPa numeric vector
TITa numeric vector
TATa numeric vector
TEYa numeric vector
CDPa numeric vector
COa numeric vector
NOXa numeric vector
Details
The dataset contains 36733 instances of 11 sensor measures aggregated over one hour, from a gas turbine located in Turkey for the purpose of studying flue gas emissions, namely CO and NOx.
Source
Heysem Kaya, Department of Information and Computing Sciences, Utrecht University, 3584 CC, Utrecht, The Netherlands
Examples
data(gt2011)
Gas-Turbine CO and NOx Emission Data
Description
Gas-Turbine CO and NOx Emission Data in 2012
Usage
data("gt2012")
Format
A data frame with 7628 observations on the following 11 variables.
ATa numeric vector
APa numeric vector
AHa numeric vector
AFDPa numeric vector
GTEPa numeric vector
TITa numeric vector
TATa numeric vector
TEYa numeric vector
CDPa numeric vector
COa numeric vector
NOXa numeric vector
Details
The dataset contains 36733 instances of 11 sensor measures aggregated over one hour, from a gas turbine located in Turkey for the purpose of studying flue gas emissions, namely CO and NOx.
Source
Heysem Kaya, Department of Information and Computing Sciences, Utrecht University, 3584 CC, Utrecht, The Netherlands
Examples
data(gt2012)
Gas-Turbine CO and NOx Emission Data
Description
Gas-Turbine CO and NOx Emission Data in 2013
Usage
data("gt2013")
Format
A data frame with 7152 observations on the following 11 variables.
ATa numeric vector
APa numeric vector
AHa numeric vector
AFDPa numeric vector
GTEPa numeric vector
TITa numeric vector
TATa numeric vector
TEYa numeric vector
CDPa numeric vector
COa numeric vector
NOXa numeric vector
Details
The dataset contains 36733 instances of 11 sensor measures aggregated over one hour, from a gas turbine located in Turkey for the purpose of studying flue gas emissions, namely CO and NOx.
Source
Heysem Kaya, Department of Information and Computing Sciences, Utrecht University, 3584 CC, Utrecht, The Netherlands
Examples
data(gt2013)
Gas-Turbine CO and NOx Emission Data
Description
Gas-Turbine CO and NOx Emission Data in 2014
Usage
data("gt2014")
Format
A data frame with 7158 observations on the following 11 variables.
ATa numeric vector
APa numeric vector
AHa numeric vector
AFDPa numeric vector
GTEPa numeric vector
TITa numeric vector
TATa numeric vector
TEYa numeric vector
CDPa numeric vector
COa numeric vector
NOXa numeric vector
Details
The dataset contains 36733 instances of 11 sensor measures aggregated over one hour, from a gas turbine located in Turkey for the purpose of studying flue gas emissions, namely CO and NOx.
Source
Heysem Kaya, Department of Information and Computing Sciences, Utrecht University, 3584 CC, Utrecht, The Netherlands
Examples
data(gt2014)
Gas-Turbine CO and NOx Emission Data
Description
Gas-Turbine CO and NOx Emission Data in 2015
Usage
data("gt2015")
Format
A data frame with 7384 observations on the following 11 variables.
ATa numeric vector
APa numeric vector
AHa numeric vector
AFDPa numeric vector
GTEPa numeric vector
TITa numeric vector
TATa numeric vector
TEYa numeric vector
CDPa numeric vector
COa numeric vector
NOXa numeric vector
Details
The dataset contains 36733 instances of 11 sensor measures aggregated over one hour, from a gas turbine located in Turkey for the purpose of studying flue gas emissions, namely CO and NOx.
Source
Heysem Kaya, Department of Information and Computing Sciences, Utrecht University, 3584 CC, Utrecht, The Netherlands
Examples
data(gt2015)