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rxCovCor: Covariance/Correlation Matrix

  • 아티클

Description

Calculate the covariance, correlation, or sum of squares / cross-product matrix for a set of variables.

Usage

  rxCovCor(formula, data, pweights = NULL, fweights = NULL, rowSelection = NULL,
           transforms = NULL, transformObjects = NULL,
           transformFunc = NULL, transformVars = NULL,
           transformPackages = NULL,transformEnvir = NULL, 
         keepAll = TRUE, varTol = 1e-12, type = "Cov",
           blocksPerRead = rxGetOption("blocksPerRead"),
           reportProgress = rxGetOption("reportProgress"), verbose = 0, 
           computeContext = rxGetOption("computeContext"), ...)

  rxCov(formula, data, pweights = NULL, fweights = NULL, rowSelection = NULL,
        transforms = NULL, transformObjects = NULL,
        transformFunc = NULL, transformVars = NULL,
        transformPackages = NULL, transformEnvir = NULL,
        keepAll = TRUE, varTol = 1e-12,
        blocksPerRead = rxGetOption("blocksPerRead"),
        reportProgress = rxGetOption("reportProgress"), verbose = 0,
        computeContext = rxGetOption("computeContext"), ...)

  rxCor(formula, data, pweights = NULL, fweights = NULL, rowSelection = NULL,
        transforms = NULL, transformObjects = NULL, 
        transformFunc = NULL, transformVars = NULL,
        transformPackages = NULL, transformEnvir = NULL, 
         keepAll = TRUE, varTol = 1e-12,
        blocksPerRead = rxGetOption("blocksPerRead"),
        reportProgress = rxGetOption("reportProgress"), verbose = 0,
        computeContext = rxGetOption("computeContext"), ...)

  rxSSCP(formula, data, pweights = NULL, fweights = NULL, rowSelection = NULL,
         transforms = NULL, transformObjects = NULL, 
         transformFunc = NULL, transformVars = NULL,
         transformPackages = NULL, transformEnvir = NULL, 
         keepAll = TRUE, varTol = 1e-12,
         blocksPerRead = rxGetOption("blocksPerRead"),
         reportProgress = rxGetOption("reportProgress"), verbose = 0, 
         computeContext = rxGetOption("computeContext"), ...)

 ## S3 method for class `rxCovCor':
print  (x, header = TRUE, ...)

Arguments

formula

formula, as described in rxFormula, with all the terms on the right-hand side of the ~ separated by + operators. Each term may be a single variable, a transformed variable, or the interaction of (transformed) variables separated by the : operator. e.g. ~ x1 + log(x2) + x3 : x4

data

either a data source object, a character string specifying a .xdf file, or a data frame object.

pweights

character string specifying the variable to use as probability weights for the observations. Only one of pweights and fweights may be specified at a time.

fweights

character string specifying the variable to use as frequency weights for the observations. Only one of pweights and fweights may be specified at a time.

rowSelection

name of a logical variable in the data set (in quotes) or a logical expression using variables in the data set to specify row selection. For example, rowSelection = "old" will use only observations in which the value of the variable old is TRUE. rowSelection = (age > 20) & (age < 65) & (log(income) > 10) will use only observations in which the value of the age variable is between 20 and 65 and the value of the log of the income variable is greater than 10. The row selection is performed after processing any data transformations (see the arguments transforms or transformFunc). As with all expressions, rowSelection can be defined outside of the function call using the expression function.

transforms

an expression of the form list(name = expression, ...) representing the first round of variable transformations. As with all expressions, transforms (or rowSelection) can be defined outside of the function call using the expression function.

transformObjects

a named list containing objects that can be referenced by transforms, transformsFunc, and rowSelection.

transformFunc

variable transformation function. See rxTransform for details.

transformVars

character vector of input data set variables needed for the transformation function. See rxTransform for details.

transformPackages

character vector defining additional R packages (outside of those specified in rxGetOption("transformPackages")) to be made available and preloaded for use in variable transformation functions, e.g., those explicitly defined in RevoScaleR functions via their transforms and transformFunc arguments or those defined implicitly via their formula or rowSelection arguments. The transformPackages argument may also be NULL, indicating that no packages outside rxGetOption("transformPackages") will be preloaded.

transformEnvir

user-defined environment to serve as a parent to all environments developed internally and used for variable data transformation. If transformEnvir = NULL, a new "hash" environment with parent baseenv() is used instead.

keepAll

logical value. If TRUE, all of the columns are kept in the returned matrix. If FALSE, columns (and corresponding rows in the returned matrix) that are symbolic linear combinations of other columns, see alias, are dropped.

varTol

numeric tolerance used to identify columns in the data matrix that have near zero variance. If the variance of a column is less than or equal to varTol and keepAll=TRUE, that column is dropped from the data matrix.

type

character string specifying the type of matrix to return. The supported types are:

  • "SSCP": Sums of Squares / Cross Products matrix.
  • "Cov": covariance matrix.
  • "Cor": correlation matrix.
    The type argument is case insensitive, e.g. "SSCP" and "sscp" are equivalent.

blocksPerRead

number of blocks to read for each chunk of data read from the data source.

reportProgress

integer value with options:

  • 0: no progress is reported.
  • 1: the number of processed rows is printed and updated.
  • 2: rows processed and timings are reported.
  • 3: rows processed and all timings are reported.

verbose

integer value. If 0, no additional output is printed. If 1, additional summary information is printed.

computeContext

a valid RxComputeContext. The RxSpark and RxHadoopMR compute contexts distribute the computation among the nodes specified by the compute context; for other compute contexts, the computation is distributed if possible on the local computer.

...

additional arguments to be passed directly to the Revolution Compute Engine.

x

an object of class "rxCovCor".

logical value. If TRUE, header information is printed.

Details

The rxCovCor, and the appropriate convenience functions rxCov, rxCor and rxSSCP, calculates either the covariance, Pearson's correlation, or a sums of squares/cross-product matrix, which may or may not use probability or frequency weights.

The sums of squares/cross-product matrix differs from the other two output types in that an initial column of 1s or square root of the weights, if specified, is added to the data matrix prior to multiplication so the first row and first column must be dropped from the output to obtain the cross-product of just the specified data matrix.

Value

For rxCovCor, an object of class "rxCovCor" with the following list elements:

CovCor

numeric matrix representing either the (weighted) covariance, correlation, or sum of squares/cross-product.

StdDevs

For type = "Cor" and "Cov", numeric vector of (weighted) standard deviations of the columns. For type = "SSCP", the standard deviations are not calculated and the return value is numeric(0).

Means

numeric vector containing the (weighted) column means.

valid.obs

number of valid observations.

missing.obs

number of missing observations.

SumOfWeights

either the sum of the weights or NA if no weights are specified.

DroppedVars

character vector containing the names of the data columns that were dropped during the calculations.

DroppedVarIndexes

integer vector containing the indices of the data columns that were dropped during the calculations.

params

parameters sent to Microsoft R Services Compute Engine.

call

the matched call.

formula

formula as described in rxFormula.

For rxCov, a covariance matrix.

For rxCor, a correlation matrix.

For rxSSCP, a sum of squares/cross-product matrix.

Author(s)

Microsoft Corporation Microsoft Technical Support

See Also

cov, cor, rxCovData, rxCorData.

Examples


 # Obtain all components from rxCovCor
 form <- ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width
 allCov <- rxCovCor(form, data = iris, type = "Cov")
 allCov

 # Direct access to covariance or correlation matrix
 rxCov(form, data = iris, reportProgress = 0)
 cov(iris[,1:4])
 rxCor(form, data = iris, reportProgress = 0)
 cor(iris[,1:4])

 # Cross-product of data matrix (need to drop first row and column of output)
 rxSSCP(form, data = iris, reportProgress = 0)[-1, -1]
 crossprod(as.matrix(iris[,1:4]))