Suppose Y1 , , Yn are independent random
Let f (yi ; i , ) be PMF or PDF of Yi , where
is a scale parameter.
If we can write
[ y b()
f (yi ; i , ) = exp
+ c(y, )],
then we call the PMF or the PDF f (yi ; i ) is
For binomial or Poisson distribution, the variance is determined if the expected value is known.
Sometimes in real application, we observe a deviance of a Pearson goodness of t much larger
than the expected if we assume the binomial or Pois
January 6, 2015
Functions of Survival Time
Let T be the survival time for a subject. Then P [T < 0] = 0 and T is a continuous random
variable. The Survival function is dened as
S(t) = P [T > t] = 1 F (t).
It is clear that S(0)
ADVANCED STATISTICAL METHODOLOGY (STAT 526)
MIDTERM EXAM (SMTH 118)
8:00-10:00PM, MONDAY, MARCH 09, 2015
There are totally 32 points in the exam. The students with score higher than or equal to 30
points will receive 30 points. Please write down your name
# Random Effect
pulp <- read.table("c:\tonglinzhang\stat526\pulp.txt",h=T)
# This is onw-way model. The first variable is response and
# the second one is the covariate variable.
op <- options(contrasts=c("contr.sum", "contr.poly")
lmod <- ao
# Section 9.1
psid <- read.table("d:\stat526\ascdata\psid.txt",h=T)
# The data psid has 1661 observations. The last column tells us how many persons involv