Help for package DLEGFM

Type:

Package

Version:

0.4.0

Title:

Distributed Loading Estimation for General Factor Model

Depends:

R (≥ 3.5.0)

Suggests:

testthat (≥ 3.0.0)

Description:

The load estimation method is based on a general factor model to solve the estimates of load and specific variance. The philosophy of the package is described in Guangbao Guo. (2022). <doi:10.1007/s00180-022-01270-z>.

License:

MIT + file LICENSE

Encoding:

UTF-8

RoxygenNote:

7.2.3

Imports:

elasticnet, stats

LazyData:

true

Config/testthat/edition:

NeedsCompilation:

Packaged:

2024-02-21 12:42:58 UTC; 17993

Author:

Guangbao Guo [aut, cre, cph], Yaping Li [aut]

Maintainer:

Guangbao Guo <ggb11111111@163.com>

Repository:

CRAN

Date/Publication:

2024-02-22 21:00:07 UTC

Loading Estimation for General Factor Model

Description

This function estimates the load and residual terms based on the general factor model and calculates the estimated values.

Usage

BlPC(data,m)

Arguments

data

The data is total data set

m

The m is the number of first layer principal component

Value

ABr

estimation of load value

ABc

estimation of load value

DBr

estimation of error term

DBc

estimation of error term

SigmaB1hat

estimation of covariance

SigmaB2hat

estimation of covariance

Author(s)

Guangbao Guo, Yaping Li

Examples

BlPC(data=ISE,m=3)

Distributed Loading Estimation for General Factor Model

Description

This function estimates the load and residual terms based on the general factor model and calculates the estimated values.

Usage

DBlPC(data,m,n1,K)

Arguments

data

The data is total data set

m

The m is the number of first layer principal component

n1

The n1 is the length of each data subset

K

The K is the number of nodes

Value

ABr

estimation of load value

ABc

estimation of load value

DBr

estimation of error term

DBc

estimation of error term

SigmaB1hat

estimation of covariance

SigmaB2hat

estimation of covariance

Author(s)

Guangbao Guo, Yaping Li

Examples

DBlPC(data=ISE,m=3,n1=107,K=5)

Distributed Loading Estimation for General Factor Model

Description

This function estimates the load and residual terms based on the general factor model and calculates the estimated values.

Usage

DFanPC(data,m,n1,K)

Arguments

data

The data is total data set

m

The m is the number of principal component

n1

The n1 is the length of each data subset

K

The K is the number of nodes

Value

AF

estimation of load value

DF

estimation of error term

SigmahatF

estimation of covariance

Author(s)

Guangbao Guo, Yaping Li

Examples

DFanPC(data=ISE,m=3,n1=107,K=5)

Distributed Loading Estimation for General Factor Model

Description

This function estimates the load and residual terms based on the general factor model and calculates the estimated values.

Usage

DGaoPC(data,m,n1,K)

Arguments

data

The data is total data set

m

The m is the number of first layer principal component

n1

The n1 is the length of each data subset

K

The K is the number of nodes

Value

AG1

estimation of load value

AG2

estimation of load value

DG1

estimation of error term

DG2

estimation of error term

SigmahatG1

estimation of covariance

SigmahatG2

estimation of covariance

Author(s)

Guangbao Guo, Yaping Li

Examples

DGaoPC(data=ISE,m=3,n1=107,K=5)

Distributed Loading Estimation for General Factor Model

Description

This function estimates the load and residual terms based on the general factor model and calculates the estimated values.

Usage

DGulPC(data,m,n1,K)

Arguments

data

The data is total data set

m

The m is the number of first layer principal component

n1

The n1 is the length of each data subset

K

The K is the number of nodes

Value

AU1

estimation of load value

AU2

estimation of load value

DU3

estimation of error term

S1hat

estimation of covariance

Author(s)

Guangbao Guo, Yaping Li

Examples

DGulPC(data=ISE,m=3,n1=107,K=5)

Dow Jones industrial average

Description

The Dow Jones industrial average (DJIA) data set.

Usage

data("DJIA")

Format

GAS.F: a numeric vector
Nikkei.F: a numeric vector
NZD: a numeric vector
silver.F: a numeric vector
RUSSELL.F: a numeric vector
S.P.F: a numeric vector
CHF: a numeric vector
Dollar.index.F: a numeric vector
Dollar.index: a numeric vector
wheat.F: a numeric vector
XAG: a numeric vector
XAU: a numeric vector

Details

The data set comes from the Dow Jones industrial average (PSA) data of 96 patients collected by Stanford University Medical Center. These patients all underwent radical prostatectomy.

Source

The Stanford University Medical Center.

References

Examples

data(DJIA)
## maybe str(DJIA) ; plot(DJIA) ...

Distributed Loading Estimation for General Factor Model

Description

This function estimates the load and residual terms based on the general factor model and calculates the estimated values.

Usage

DPC(data,m,n1,K)

Arguments

data

The data is total data set

m

The m is the number of first layer principal component

n1

The n1 is the length of each data subset

K

The K is the number of nodes

Value

Ahat

estimation of load value

Dhat

estimation of error term

Sigmahat

estimation of covariance

Author(s)

Guangbao Guo, Yaping Li

Examples

DPC(data=ISE,m=3,n1=107,K=5)

Distributed Loading Estimation for General Factor Model

Description

This function estimates the load and residual terms based on the general factor model and calculates the estimated values.

Usage

DPPC(data,m,n1,K)

Arguments

data

The data is total data set

m

The m is the number of first layer principal component

n1

The n1 is the length of each data subset

K

The K is the number of nodes

Value

Apro

estimation of load value

Dpro

estimation of error term

Sigmahatpro

estimation of covariance

Author(s)

Guangbao Guo, Yaping Li

Examples

DPPC(data=ISE,m=3,n1=107,K=5)

Loading Estimation for General Factor Model

Description

This function estimates the load and residual terms based on the general factor model and calculates the estimated values.

Usage

FanPC(data,m)

Arguments

data

The data is total data set

m

The m is the number of principal component

Value

AF

estimation of load value

DF

estimation of error term

SigmahatF

estimation of covariance

Author(s)

Guangbao Guo, Yaping Li

Examples

FanPC(data=ISE,m=3)

Loading Estimation for General Factor Model

Description

This function estimates the load and residual terms based on the general factor model and calculates the estimated values.

Usage

GaoPC(data,m)

Arguments

data

The data is total data set

m

The m is the number of principal component

Value

AG1

estimation of load value

AG2

estimation of load value

DG1

estimation of error term

DG2

estimation of error term

SigmahatG1

estimation of covariance

SigmahatG2

estimation of covariance

Author(s)

Guangbao Guo, Yaping Li

Examples

GaoPC(data=ISE,m=3)

Loading Estimation for General Factor Model

Description

This function estimates the load and residual terms based on the general factor model and calculates the estimated values.

Usage

GulPC(data,m)

Arguments

data

The data is total data set

m

The m is the number of first layer principal component

Value

AU1

estimation of load value

AU2

estimation of load value

DU3

estimation of error term

Shat

estimation of covariance

Author(s)

Guangbao Guo, Yaping Li

Examples

GulPC(data=ISE,m=3)

Istanbul Stock Exchange

Description

The Istanbul Stock Exchange (ISE) data set.

Usage

data("ISE")

Format

ISE: a numeric vector
SP: a numeric vector
DAX: a numeric vector
FTSE: a numeric vector
NIKKEI: a numeric vector
BOVESPA: a numeric vector
EU: a numeric vector
EM: a numeric vector

Details

The data set comes from the Istanbul Stock Exchange (ISE) data of 96 patients collected by Stanford University Medical Center. These patients all underwent radical prostatectomy.

Source

The Stanford University Medical Center.

References

Examples

data(ISE)
## maybe str(ISE) ; plot(ISE) ...

Loading Estimation for General Factor Model

Description

This function estimates the load and residual terms based on the general factor model and calculates the estimated values.

Usage

PC(data,m)

Arguments

data

The data is a highly correlated data set

m

The m is the number of principal component

Value

Ahat

estimation of load value

Dhat

estimation of error term

Sigmahat

estimation of covariance

Author(s)

Guangbao Guo, Yaping Li

Examples

PC(data=ISE,m=3)

Loading Estimation for General Factor Model

Description

This function estimates the load and residual terms based on the general factor model and calculates the estimated values.

Usage

PPC(data,m)

Arguments

data

The data is total data set

m

The m is the number of principal component

Value

Apro

estimation of load value

Dpro

estimation of error term

Sigmahatpro

estimation of covariance

Author(s)

Guangbao Guo, Yaping Li

Examples

PPC(data=ISE,m=3)

New York Stock Exchange Composite Index

Description

The New York Stock Exchange Composite Index SECI(SECI) data set.

Usage

data("SECI")

Format

GBP: a numeric vector
JPY: a numeric vector
CAD: a numeric vector
AAPL: a numeric vector
AMZN: a numeric vector
GE: a numeric vector
JPM: a numeric vector
MSFT: a numeric vector
WFC: a numeric vector
XOM: a numeric vector
FCHI: a numeric vector
FTSE: a numeric vector
GDAXI: a numeric vector

Details

The data set comes from the prostate specific antigen (PSA) data of 96 patients collected by Stanford University Medical Center. These patients all underwent radical prostatectomy.

Source

The Stanford University Medical Center.

References

Examples

data(SECI)
## maybe str(SECI) ; plot(SECI) ...

Stock Portfolio Performance

Description

The Stock Portfolio Performance (SPP) data set.

Usage

data("SPP")

Format

X1: a numeric vector
X2: a numeric vector
X3: a numeric vector
X4: a numeric vector
X5: a numeric vector
X6: a numeric vector
X7: a numeric vector
X8: a numeric vector
X9: a numeric vector
X10: a numeric vector

Details

The data set comes from the Stock Portfolio Performance (SPP) data of 96 patients collected by Stanford University Medical Center. These patients all underwent radical prostatectomy.

Source

The Stanford University Medical Center.

References

Examples

data(SPP)
## maybe str(SPP) ; plot(SPP) ...