Related articles:
Likelihood function
Normal distribution
Fisher information
Variance
Mean
Statistics
Generalized linear model
Confidence interval
Covariance matrix
Ronald Fisher
Structural equation modeling
Key terms:
sigma
estimator
likelihood
mle
theta
sample
parameter
widehat
probability
asymptotic
ldots
observations
maximize
variance
maximum likelihood estimator
mathcal
suppose
sample size
mid p
logarithm
generalized
likelihood function
binomial
stable url
approximation
random variables
tossing
gaussian
nuisance
unbiased estimator
bernoulli
fisher information
possible values
unknown parameter
covariance matrix
information matrix
expected value
probability density function
normal distribution
parameter space
mean squared error
uniform distribution
maximum a posteriori
when the sample size
sample size increases
discrete distribution
maximize the likelihood
independent identically distributed
gives heads with probability
joint probability density function
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