6.11.2.3.9. statsmodels.sandbox.tsa.diffusion.SchwartzOne

class statsmodels.sandbox.tsa.diffusion.SchwartzOne(xzero, mu, kappa, sigma)[source]

the Schwartz type 1 stochastic process

:math:: dx_t = kappa (mu - ln x_t) x_t dt + sigma x_tdW

The Schwartz type 1 process is a log of the Ornstein-Uhlenbeck stochastic process.

__init__(xzero, mu, kappa, sigma)[source]

6.11.2.3.9.1. Methods

__init__(xzero, mu, kappa, sigma)
exactdist(xzero, t)
exactprocess(xzero, nobs[, ddt, nrepl]) uses exact solution for log of process
expectedsim(func[, nobs, T, dt, nrepl]) get expectation of a function of a Wiener Process by simulation
fitls(data, dt) assumes data is 1d, univariate time series
sim([nobs, T, dt, nrepl])
simEM([xzero, nobs, T, dt, nrepl, Tratio]) from Higham 2001
simulateW([nobs, T, dt, nrepl]) generate sample of Wiener Process