Sökning: "Graphical Lasso"

Hittade 4 uppsatser innehållade orden Graphical Lasso.

  1. 1. Estimating Dependence Structures with Gaussian Graphical Models : A Simulation Study in R

    Kandidat-uppsats, Umeå universitet/Statistik

    Författare :Artem Angelchev Shiryaev; Johan Karlsson; [2021]
    Nyckelord :Simulation study; Graphical models; undirected Gaussian graphical model; Partial correlation; Precision matrix;

    Sammanfattning : Graphical models are powerful tools when estimating complex dependence structures among large sets of data. This thesis restricts the scope to undirected Gaussian graphical models. An initial predefined sparse precision matrix was specified to generate multivariate normally distributed data. LÄS MER

  3. 2. Multivariate Risk: From Univariate to High-Dimensional Graphical Models

    Magister-uppsats, Lunds universitet/Statistiska institutionen

    Författare :Erik Oldehed; [2020]
    Nyckelord :Block Maxima; Mean Excess Plot; Tail Risk; Cross-Validation Threshold Selection; Graphical Lasso; Nonparanormal Distribution.; Mathematics and Statistics;

    Sammanfattning : We present a comparison of different univariate and multivariate extreme value risk models. Our focus is on exploring how these can be used to model financial risk. We use simulated as well as real data and compare deterministic and cross-validation threshold selection methods for the GP model to a GEV model. LÄS MER

  4. 3. Storskalig nätverksestimering Utvärdering av en ny metod för glesa nätverk

    Kandidat-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaper

    Författare :Jenny Andersson; Rebecka Bertilsson; Helena Foogde; Lovisa Köllerström; Robin Lindström; [2019-06-18]
    Nyckelord :;

    Sammanfattning : Partiell korrelation mellan variabler kan implicit erhållas genom precisionsmatrisen. För att estimera denna kan den empiriska kovariansmatrisen inverteras. Problem uppstår när antalet variabler p är större än antalet observationer n, eftersom kovariansmatrisen då får låg rang och inte kan inverteras. LÄS MER

  5. 4. Graphical lasso for covariance structure learning in the high dimensional setting

    Master-uppsats, KTH/Matematisk statistik

    Författare :Viktor Fransson; [2015]
    Nyckelord :;

    Sammanfattning : This thesis considers the estimation of undirected Gaussian graphical models especially in the high dimensional setting where the true observations are assumed to be non-Gaussian distributed. The first aim is to present and compare the performances of existing Gaussian graphical model estimation methods. LÄS MER