Sökning: "Adaptive Lasso"

Visar resultat 1 - 5 av 9 uppsatser innehållade orden Adaptive Lasso.

  1. 1. Nowcasting U.S. inflation using mixed frequency real-time data

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Gustaf Lundgren; Nils Wicktor; [2023]
    Nyckelord :Inflation; Machine Learning; Nowcasting; MIDAS; Almon distributed lag models; Real-Time data; Random Forest; XGBoost; Mathematics and Statistics;

    Sammanfattning : Different models were developed with the aim of nowcasting inflation at a daily basis with high frequency variables, while using real-time data to avoid look ahead bias. Both popular machine learning models such as Random Forest and XGBoost, and more traditional models such as UMIDAS and Almon distributed lag models were used to make the nowcasts. LÄS MER

  3. 2. Predicting misuse of subscription tranquilizers : A comparasion of regularized logistic regression, Adaptive Bossting and support vector machines

    Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

    Författare :Ida Norén; [2022]
    Nyckelord :Adaptive Boosting; Benzodiazepines; classification; lasso regularization; logistic regression; support vector machines;

    Sammanfattning : Tranquilizer misuse is a behavior associated with substance use disorder. As of now there is only one published article that includes a predictive model on misuse of subscription tranquilizers. LÄS MER

  4. 3. Variabelselektion för högdimensionella data : En jämförande simuleringsstudie av variabelselektionsmetoder

    Kandidat-uppsats, Umeå universitet/Statistik

    Författare :Jesper Lindberg; Oscar Lidström; [2022]
    Nyckelord :;

    Sammanfattning : Högdimensionella data är något som blir allt vanligare inom flera områden som ekonomi, medicin och geologi. Detta kan ofta vara svårt att hantera. Det är därför viktigt att veta hur olika metoder som skattar regressionsmodeller fungerar och presterar för att kunna använda den metod som passar bäst utefter det syfte som finns. LÄS MER

  5. 4. Variable Selection in High-Dimensional Data

    Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Sarah Reichhuber; Johan Hallberg; [2021]
    Nyckelord :variable selection; variable selection methods; linear regression; high-dimensional data; variable importance;

    Sammanfattning : Estimating the variables of importance in inferentialmodelling is of significant interest in many fields of science,engineering, biology, medicine, finance and marketing. However,variable selection in high-dimensional data, where the number ofvariables is relatively large compared to the observed data points,is a major challenge and requires more research in order toenhance reliability and accuracy. LÄS MER

  7. 5. Comparison of existing ZOI estimation methods with different model specifications and data.

    Master-uppsats, Högskolan Dalarna/Mikrodataanalys

    Författare :Shraddha Mukhopadhyay; [2020]
    Nyckelord :Zone of Influence; reindeer; pellet group count; logistic regression; segmented model; Hierarchical Likelihood; Adaptive Lasso; threshold; breakpoint;

    Sammanfattning : With the increasing demand and interest in wind power worldwide, it is interesting to study the effects of running windfarms on the activity of reindeers and estimate the associated Zone of Influence (ZOI) relative to these disturbances. Through simulation, Hierarchical Likelihood (HL) and adaptive Lasso methods are used to estimate the ZOI of windfarms and catching the correct threshold at which the negative effect of the disturbances on the reindeer behaviour disappears. LÄS MER