| PRTools contents |
GENDATP
B = GENDATP(A,N,S,G)
| Input | |
| A | Dataset |
| N | Number(s) of points to be generated (optional; default: 50 per class) |
| S | Smoothing parameter(s) (optional; default: a maximum likelihood estimate based on A) |
| G | Covariance matrix used for generation of the data (optional; default: the identity matrix) |
| Output | |
| B | Dataset of points generated according to Parzen density |
Generation of a dataset B of N points by using the Parzen estimate of the density of A based on a smoothing parameter S. N might be a row/column vector with different numbers for each class. Similarly, S might be a vector with different smoothing parameters for each class. If S = 0, then S is determined by a maximum likelihood estimate using PARZENML. If N is a vector, then exactly N(I) objects are generated for the class I. G is the covariance matrix to be used for generating the data. G may be a 3-dimensional matrix storing separate covariance matrices for each class.
| PRTools contents |