Suppose that W, the amount of moisture in the air on a given day, is a gamma random variable with parameters ( t , β ) . That is, its density is f ( ω ) = β e − β ω ( β ω ) t − 1 Γ ( t ) , ω > 0 . Suppose also that given that W = ω . the number of accidents during that day—call it N—has a Poisson distribution with mean ω . Show that the conditional distribution of W given that N = n is the gamma distribution with parameters ( t + n , β + 1 ) .
Suppose that W, the amount of moisture in the air on a given day, is a gamma random variable with parameters ( t , β ) . That is, its density is f ( ω ) = β e − β ω ( β ω ) t − 1 Γ ( t ) , ω > 0 . Suppose also that given that W = ω . the number of accidents during that day—call it N—has a Poisson distribution with mean ω . Show that the conditional distribution of W given that N = n is the gamma distribution with parameters ( t + n , β + 1 ) .
Suppose that W, the amount of moisture in the air on a given day, is a gamma random variable with parameters
(
t
,
β
)
. That is, its density is
f
(
ω
)
=
β
e
−
β
ω
(
β
ω
)
t
−
1
Γ
(
t
)
,
ω
>
0
. Suppose also that given that
W
=
ω
. the number of accidents during that day—call it N—has a Poisson distribution with mean
ω
. Show that the conditional distribution of
W given that
N
=
n
is the gamma distribution with parameters
(
t
+
n
,
β
+
1
)
.
An entomologist is studying a rare type of insect. He finds that the time from birth until death (in years,
denoted by T) of a randomly selected member of this insect population has a Gamma distribution with
parameters a = 2 and B = 6.
Find the average life of a random insect of this type.
Find the probability that one of this random insects survives longer than 20 years.
Suppose data are positive numbers a1, 2, . .., T, and suppose it is decided to model these by i.i.d. random
variables X1, X2, ..., X, with common Gamma(v, A) distribution as described in Definition 3.12 of the notes.
Here the shape parameter v is supposed to be known, but the rate parameterdE (0, 00) is unknown and needs to
be estimated. Let Å be the MLE for A. Setting i = , e;, which of the following statements is true?
O i=7/v.
O If Z is defined by substituting X; for æ; in A, then Z1 has a Gamma(nv, A) distribution.
O If Z is defined by substituting X; for a; in Ä, then Z-1 has a Gamma(nv, nvd) distribution.
O If Z is defined by substituting X; for æ; in A, then Z has a Gamma(nv, A/(nv)) distribution.
O Â=v/T.
O î = (2)".
O If Z is defined by substituting X; for æ; in A, then Z has a Gamma(nv, X) distribution.
Let X be a continuous random variable with mean μ and standard deviation σ. If X is transformed to Y = 2X + 3, what are the mean and standard deviation of Y?
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, probability and related others by exploring similar questions and additional content below.