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1
Missing and modified data in nonparametric estimation
CRC Press
Efromovich
,
Sam
estimator
density
regression
estimation
sample
function
figure
estimate
underlying
observations
diagram
random
ϕj
fourier
shown
analysis
nonparametric
shows
availability
survival
likelihood
variance
consider
responses
rate
probability
efromovich
variables
predictors
censoring
statistical
censored
diagrams
interest
hazard
estimated
functions
observed
cases
estimates
simulation
spectral
parameters
biased
bernoulli
recall
corresponding
proposed
dashed
θj
Year:
2018
Language:
english
File:
PDF, 84.25 MB
Your tags:
0
/
0
english, 2018
2
Nonparametric Curve Estimation: Methods, Theory and Applications
Springer
Yiannis Moschovakis
estimate
function
density
figure
estimator
estimation
regression
functions
underlying
shown
random
sample
nonparametric
estimates
coefficients
consider
universal
optimal
recall
probability
kernel
fourier
defined
discussed
shows
observations
analysis
estimated
errors
approximation
linear
error
noise
standard
variance
squared
diagram
values
wavelet
approach
component
samples
corresponding
signal
scale
rate
densities
method
interval
components
Year:
1999
Language:
english
File:
PDF, 25.64 MB
Your tags:
0
/
0
english, 1999
3
Nonparametric Curve Estimation: Methods, Theory and Applications
Springer
Sam Efromovich
estimate
function
density
figure
estimator
estimation
regression
functions
underlying
shown
random
nonparametric
sample
estimates
coefficients
ϕj
universal
consider
θj
optimal
recall
observations
probability
kernel
first
fourier
defined
discussed
shows
estimated
analysis
different
approximation
errors
linear
θ̂j
error
noise
standard
component
variance
values
find
squared
diagram
wavelet
monotone
approach
corresponding
samples
Year:
1999
Language:
english
File:
PDF, 4.80 MB
Your tags:
0
/
0
english, 1999
4
Nonparametric curve estimation: methods, theory and applications
Springer
Sam Efromovich
estimate
function
density
figure
estimator
estimation
regression
functions
underlying
shown
random
nonparametric
sample
estimates
coefficients
ϕj
universal
consider
θj
optimal
recall
observations
probability
kernel
first
fourier
defined
discussed
shows
estimated
analysis
different
approximation
errors
linear
θ̂j
error
noise
standard
component
variance
values
find
squared
diagram
wavelet
monotone
approach
corresponding
samples
Year:
1999
Language:
english
File:
PDF, 3.28 MB
Your tags:
0
/
0
english, 1999
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