Isotonic regression in deterministic and random design settings
(2016) MASM01 20161Mathematical Statistics
- Abstract (Swedish)
- This thesis will treat the subject of constrained statistical inference
and will have its focus on isotonic regression, which is the problem of
estimating functions that are assumed to be monotone.
A characterisation of isotonic regression and a solution to this problem
will be given. The PAVA algorithm to compute the isotonic regres-
sion estimator will be introduced along with asymptotic distribution
results for this. The aim is to investigate the properties of the esti-
mator when the observation points are random dependent variables
which also depend on the unknown function itself.
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8568359
- author
- Jönsson, Viktor
- supervisor
- organization
- course
- MASM01 20161
- year
- 2016
- type
- H2 - Master's Degree (Two Years)
- subject
- language
- English
- id
- 8568359
- date added to LUP
- 2016-01-26 11:42:04
- date last changed
- 2016-01-26 11:42:04
@misc{8568359, abstract = {{This thesis will treat the subject of constrained statistical inference and will have its focus on isotonic regression, which is the problem of estimating functions that are assumed to be monotone. A characterisation of isotonic regression and a solution to this problem will be given. The PAVA algorithm to compute the isotonic regres- sion estimator will be introduced along with asymptotic distribution results for this. The aim is to investigate the properties of the esti- mator when the observation points are random dependent variables which also depend on the unknown function itself.}}, author = {{Jönsson, Viktor}}, language = {{eng}}, note = {{Student Paper}}, title = {{Isotonic regression in deterministic and random design settings}}, year = {{2016}}, }