Suppose a function f : R → R is continuous with f(0) = 1. Show
that if there is a positive number x0 for which
f(x0) = 0, then there is a smallest positive number p
for which f(p) = 0. (Hint: Consider the set {x | x > 0, f(x) =
0}.)
Let T > 0 be a continuous random variable with cumulative
hazard function H(·).
Show that H(T)∼Exp(1),where Exp(λ) in general denotes the
exponential distribution with rate parameter λ.
Hints:
(a) You can use the following fact without proof: For any
continuous random variable T with cumulative distribution function
F(·), F(T) ∼ Unif(0,1). Hence S(T) ∼ Unif(0,1).
(b) Use the relationship between S(t) and H(t) to derive that
Pr(H(T) > x)= e−x.
Let f be a differentiable function on the interval [0, 2π] with
derivative f' . Show that there exists a point c ∈ (0, 2π) such
that cos(c)f(c) + sin(c)f'(c) = 2 sin(c).
(A universal random number generator.)Let X have a continuous,
strictly increasing cdf F. Let Y = F(X). Find the density of Y.
This is called the probability integral transform. Now let U ∼
Uniform(0,1) and let X = F−1(U). Show that X ∼ F. Now write a
program that takes Uniform (0,1) random variables and generates
random variables from an Exponential (β) distribution
How logistic regression maps all outcome to either 0 or 1. The
equation for log-likelihood
function (LLF) is :
LLF = Σi( i log( ( i)) + (1 − i) log(1 − ( i))). y p x y p x
How logistic regression uses this in maximum likelihood
estimation?
Show that the transformation w = z ^1/ 2 maps usually maps
vertical and horizontal lines onto portions of hyperbolas.
Investigate the lines x = a, y = b for the cases
1) a > 0, b > 0,
2) a = b =0
f(t) = 1- t 0<t<1
a function f(t) defined on an interval 0 < t < L is given.
Find the Fourier cosine and sine series of f and sketch the graphs
of the two extensions of f to which these two series converge