Syntax

Arguments and performed function

W = exp(X);

W is a matrix with entries equal to the exponentials of the entries of X. The function works element-wise.

• X must be a matrix or dataset

W = log(X);

W is a matrix with entries equal to the natural logarithms of the entries of X. The function works element-wise.

• X must be a matrix or dataset
• If X contains non-positive entries then the corresponding entries of W are set to nan

W = sqrt(X);

W is a matrix with entries equal to the square roots of the entries of X. The function works element-wise.

• X must be a matrix or dataset
• If X contains negative entries then the corresponding entries of W are set to nan

W = abs(X);

W is a matrix with entries equal to the absolute values of the entries of X. The function works element-wise.

• X must be a matrix or dataset

W = mod(X, Y);

W is a matrix with entries equal to modula of the element-wise division X./Y

• X must be a matrix or dataset
• Y must be a matrix or dataset
• The dimensions of X and Y must be equal

W = sin(X);

W is a matrix with entries equal to the sines of the entries of X. The function works element-wise.

• X must be a matrix or dataset

W = cos(X);

W is a matrix with entries equal to cosines of the entries of X. The function works element-wise.

• X must be a matrix or dataset

W = tan(X);

W is a matrix with entries equal to the tangents of the entries of X. The function works element-wise.

• X must be a matrix or dataset

W = asin(X);

W is a matrix with entries equal to the arcsines of the entries of X. The function works element-wise.

• X must be a matrix or dataset
• If X contains entries outside the interval $\left[-1,1\right]$ then the corresponding entries of W are set to nan

W = acos(X);

W is a matrix with entries equal to the arccosines of the entries of X. The function works element-wise.

• X must be a matrix or dataset
• If X contains entries outside the interval $\left[-1,1\right]$ then the corresponding entries of W are set to nan

W = atan(X);

W is a matrix with entries equal to the arctangents of the entries of X. The function works element-wise.

• X must be a matrix or dataset

W = inv(X);

W is the inverse of X.

• X must be a square matrix or dataset
• If X is singular an error is produced

W = invpd(X);

W is the inverse of X, where X is symmetric and positive definite. This function works faster and is more precise than the general inv() function, taking advantage of the structure of X.

• X must be a symmetric and positive-definite matrix or dataset
• If X is not positive definite an error is produced

W = det(X);

W is an $1\times 1$ matrix with value equal to the determinant of X.

• X must be a square matrix

W = trace(X);

W is an $1\times 1$ matrix with value equal to the trace of X.

• X must be a square matrix

W = diag(X);

The function’s return value depends on the size of X:
$\to$ if X is an $M\times M$ matrix then W is an $M\times 1$ vector that contains the values on the diagonal of X
$\to$ if X is vector of length $M$ then W is a diagonal $M\times M$ matrix that contains the entries of X on its diagonal.

• X must be either a square matrix (or dataset) or a vector