Understand your Mac and iPhone more deeply by tracing the evolution of Mac OS X from prelease to Swift. John Siracusa delivers the details.
You've got two main options:
| # prior - likelihood conflict | |
| library(rethinking) | |
| yobs <- 0 | |
| mtt <- ulam( | |
| alist( | |
| y ~ dstudent(2,mu,1), | |
| mu ~ dstudent(2,10,1) |
| import numpy as np | |
| import pylab as pl | |
| from numpy import fft | |
| def fourierExtrapolation(x, n_predict): | |
| n = x.size | |
| n_harm = 10 # number of harmonics in model | |
| t = np.arange(0, n) | |
| p = np.polyfit(t, x, 1) # find linear trend in x | |
| x_notrend = x - p[0] * t # detrended x |