| qr_decomposition | R Documentation |
These functions mimic the base qr family functions to operate on gpu.matrix-class objects.
## S4 method for signature 'gpu.matrix.tensorflow'
qr(x,...)
## S4 method for signature 'gpu.matrix.torch'
qr(x,...)
## S4 method for signature 'list'
qr.Q(qr,complete,Dvec)
## S4 method for signature 'list'
qr.R(qr,complete)
## S4 method for signature 'list'
qr.X(qr,complete)
## S4 method for signature 'list'
qr.coef(qr,y)
## S4 method for signature 'list'
qr.qy(qr,y)
## S4 method for signature 'list'
qr.qty(qr,y)
## S4 method for signature 'list'
qr.resid(qr,y)
## S4 method for signature 'ANY,gpu.matrix.tensorflow'
qr.solve(a,b)
## S4 method for signature 'ANY,gpu.matrix.torch'
qr.solve(a,b)
## S4 method for signature 'gpu.matrix.tensorflow,ANY'
qr.solve(a,b)
## S4 method for signature 'gpu.matrix.tensorflow,gpu.matrix.tensorflow'
qr.solve(a,b)
## S4 method for signature 'gpu.matrix.torch,ANY'
qr.solve(a,b)
## S4 method for signature 'gpu.matrix.torch,gpu.matrix.torch'
qr.solve(a,b)
## S4 method for signature 'list,ANY'
qr.solve(a,b)
x |
a |
y, b |
a |
... |
further arguments passed to or from other methods. |
qr |
a list resulting from the application of the function |
complete |
The same as in 'base' function |
Dvec |
The same as in 'base' function |
a |
a |
The function qr internally calls the corresponding function of the library torch or tensorflow (depending on the type of input gpu.matrix-class).
The QR decomposition can be used to solve the equation Ax=b for a given matrix A, and a vector of observations b. In this context, the functions qr.coef, and qr.resid return the coefficients, and residuals values. Moreover, the functions qr.qy, and qr.qty returns Q %*% y and Q %*% t(y).
Note that if parameter complete is TRUE then an arbitrary orthogonal completion of the X and Q matrix or wheter the R matrix is to be completed by binding zero-value rows beneath the square upper triangle.
The function solve.qr solves the system of equations Ax=b via the QR decomposition. This function internally calls the corresponding function of the library torch or tensorflow (depending on the type of input gpu.matrix-class).
If the input gpu.matrix-class object(s) are stored on the GPU, then the operations will be performed on the GPU. See gpu.matrix.
The function qr returns a list with the following items:
q |
The corresponding complete matrix |
r |
The corresponding complete matrix |
x |
The matrix |
Please note that the output returned by this function is different from the 'base' function qr, which returns an object of the 'qr' class.
After performing a QR decomposition on a matrix A, given the resulting object, the functions qr.X, qr.Q, and qr.R return the original matrix A, the matrix Q, and the matrix R respectively. The returned matrices are gpu.matrix-class objects.
The functions qr.coef and qr.resid return the coefficients and residuals when fitting the equation Ax=b. In this context, the functions qr.qy, and qr.qty returns Q %*% y and Q %*% t(y). The resulting vectors are objects of the class gpu.matrix.
The function qr.solve returns a gpu.matrix-class object containing the coefficients of the solution of the system of equations Ax=b by QR decomposition.
See qr, linalg_qr, torch_triangular_solve
## Not run:
## overdetermined system
A <- gpu.matrix(runif(12),nrow = 4)
b <- gpu.matrix(rnorm(4),ncol=1)
qr.solve(a = A, b)
qr_gpu <- qr(A)
qr.solve(a=qr_gpu,b)
qr.coef(qr = qr_gpu,b)
qr.resid(qr = qr_gpu,b)
qr.qty(qr = qr_gpu,b)
qr.qy(qr = qr_gpu,b)
qr.X(qr = qr_gpu,complete = T)
qr.Q(qr = qr_gpu,complete = T)
qr.R(qr = qr_gpu,complete = T)
## underdetermined system
A <- gpu.matrix(runif(12),nrow = 3)
b <- gpu.matrix(rnorm(3),ncol=1)
qr.solve(a = A, b)
qr_gpu <- qr(A)
qr.solve(a=qr_gpu,b)
qr.coef(qr = qr_gpu,b)
qr.resid(qr = qr_gpu,b)
qr.qty(qr = qr_gpu,b)
qr.qy(qr = qr_gpu,b)
qr.X(qr = qr_gpu,complete = T)
qr.Q(qr = qr_gpu,complete = T)
qr.R(qr = qr_gpu,complete = T)
## End(Not run)
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