Python代写代考

In [2]: import sympy import numpy as np import matplotlib.pyplot as plt import pynverse %matplotlib inline import pynverse In [3]: t = sympy.Symbol(‘t’) lmbda = sympy.sin(t/60) + 10 Lmbda = sympy.integrate(lmbda, (t, 0, t)) # sympy can’t solve this because there isn’t # a closed-form solution. u = sympy.Symbol(‘u’) inv_arrival = sympy.solve(Lmbda – u, t) ————————————————————————— NotImplementedError

In [1]: import sympy import numpy as np import matplotlib.pyplot as plt import scipy.special as spsp Negative Binomial Distribution is another distribution that models i.i.d. Bernoulli trials. It is used to measures the probabilities of $k$ trials in order to getting $r$ number of successes. The probability of success of each Beroulli trial is $p$. $PMF(k)=\frac{(k-1)!}{(k-r)!(r-1)!}(1-p)^{k-r}p^r,