The daily rainfall in Dublin (measured in millimeters) is modelled using a gamma distribution with parameters α = 0.8 and β = 0.4 (d) Use the central limit theorem to approximate the probability that the annual rainfall exceeds 800mm (write down the analytical formula and the code used to calculate the cdf value).
If is the
random variable representing the daily rainfall, then the random
variable representing the annual rainfall is
.
Here
. Also
According to Central Limit Theorem (CLT), approximately, the
distribution of
is
The approximate probability that the annual rainfall exceeds 800 mm is
The R commands for the above probability is
> 1-pnorm(800,mean=730,sd=sqrt(1825))
[1] 0.05065079
> 1-pnorm(1.6385761 )
[1] 0.05065079
The daily rainfall in Dublin (measured in millimeters) is modelled using a gamma distribution with parameters...
The daily rainfall in Dublin (measured in millimeters) is modelled using a gamma distribution with parameters α = 0.8 and β = 0.4. (a) Write down the distribution (pdf) of the daily rainfall in Dublin. (b) Use Markov’s inequality to upper bound the probability that the observed rainfall in a given day is larger than 3 mm, and compare the value to its true counterpart. (c) Consider the overall rainfall in 365 days, and use mgfs and their properties to...
The daily rainfall in Japan (measured in millimeters) is modelled using a gamma distribution with parameters α = 0.8 and β = 0.4. Consider the overall rainfall in 365 days, and use mgfs and their properties to prove that this is Ga (292, 0.4). Use the central limit theorem to approximate the probability that the annual rainfall exceeds 800mm (write down the analytical formula and the R code used to calculate the cdf value).
1. The daily rainfall in Dublin (measured in millimeters) is modelled using a gamma distribution with parameters α = 0.8 and β = 0.4. . (c) Consider the overall rainfall in 365 days, and use mgfs and their properties to prove that this is Ga (292, 0.4). .
(c)Claim amounts on a certain type of policy are modelled as following a gamma distribution with parameters alpha = 120 and theta = 1.2. Calculate an approximate value for the probability that an individual claim amount exceeds 120, giving a reason for the approach you use.