| reshape_vec2mat | R Documentation | 
The reshape_vec2mat function facilitates the creation of square correlation/covariance matrices from scalars or vectors of variances/covariances.
It allows the user to supply a vector of covariances that make up the lower triangle of a matrix, determines the order of the matrix necessary to hold those covariances, and constructs a matrix accordingly.
reshape_vec2mat(
  cov = NULL,
  var = NULL,
  order = NULL,
  var_names = NULL,
  by_row = FALSE,
  diag = FALSE
)
cov | 
 Scalar or vector of covariance information to include the lower-triangle positions of the matrix (default value is zero).
If a vector, the elements must be provided in the order associated with concatenated column (  | 
var | 
 Scalar or vector of variance information to include the diagonal positions of the matrix (default value is 1).  | 
order | 
 If cov and var are scalars, this argument determines the number of variables to create in the output matrix.  | 
var_names | 
 Optional vector of variable names.  | 
by_row | 
 Logical scalar indicating whether   | 
diag | 
 Logical scalar indicating whether   | 
A variance-covariance matrix
## Specify the lower triangle covariances
## Can provide names for the variables
reshape_vec2mat(cov = c(.3, .2, .4), var_names = c("x", "y", "z"))
## Specify scalar values to repeat for the covariances and variances
reshape_vec2mat(cov = .3, var = 2, order = 3)
## Give a vector of variances to create a diagonal matrix
reshape_vec2mat(var = 1:5)
## Specify order only to create identity matrix
reshape_vec2mat(order = 3)
## Specify order and scalar variance to create a scalar matrix
reshape_vec2mat(var = 2, order = 3)
## A quick way to make a 2x2 matrix for bivariate correlations
reshape_vec2mat(cov = .2)
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