Divide into *n* continuous intervals with equal probability. Returns a list of (n - 1) cut points separating the intervals. Set *n* to 4 for quartiles (the default). Set *n* to 10 for deciles. Set *n* to 100 for percentiles which gives the 99 cuts points that separ
(self, n=4)
| 1284 | return _normal_dist_inv_cdf(p, self._mu, self._sigma) |
| 1285 | |
| 1286 | def quantiles(self, n=4): |
| 1287 | """Divide into *n* continuous intervals with equal probability. |
| 1288 | |
| 1289 | Returns a list of (n - 1) cut points separating the intervals. |
| 1290 | |
| 1291 | Set *n* to 4 for quartiles (the default). Set *n* to 10 for deciles. |
| 1292 | Set *n* to 100 for percentiles which gives the 99 cuts points that |
| 1293 | separate the normal distribution in to 100 equal sized groups. |
| 1294 | """ |
| 1295 | return [self.inv_cdf(i / n) for i in range(1, n)] |
| 1296 | |
| 1297 | def overlap(self, other): |
| 1298 | """Compute the overlapping coefficient (OVL) between two normal distributions. |