Sökning: "Regression model"

Visar resultat 1 - 5 av 864 avhandlingar innehållade orden Regression model.

  1. 1. Model Selection and Sparse Modeling

    Författare :Yngve Selén; Peter Stoica; Jean-Jacques Fuchs; Uppsala universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; model selection; model order selection; model averaging; nested models; sparse models; Bayesian inference; MMSE estimation; MAP estimation; ML estimation; AIC; BIC; GIC; RAKE receivers; pulse compression; radar; linear models; linear regression models; Signal processing; Signalbehandling;

    Sammanfattning : Parametric signal models are used in a multitude of signal processing applications. This thesis deals with signals for which there are many candidate models, and it is not a priori known which model is the most appropriate one. LÄS MER

  3. 2. Multivariate Aspects of Phylogenetic Comparative Methods

    Författare :Krzysztof Bartoszek; Göteborgs universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; General Linear Model; Ornstein-Uhlenbeck process; Multivariate phylogenetic comparative method; Evolutionary model; Adaptation; Optimality; Measurement error; Regression; Adaptation; Major-axis regression; Reduced major-axis regression; Structural equation; Allometry; Phylogenetic inertia; Allometry;

    Sammanfattning : his thesis concerns multivariate phylogenetic comparative methods. We investigate two aspects of them. The first is the bias caused by measurement error in regression studies of comparative data. We calculate the formula for the bias and show how to correct for it. LÄS MER

  4. 3. Generalization under Model Mismatch and Distributed Learning

    Författare :Martin Hellkvist; Ayca Özcelikkale; Anders Ahlén; Martin Jaggi; Uppsala universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Machine learning; Signal processing; Generalization error; Training error; Double-descent; Double descent; Distributed learning; Distributed optimization; Learning over networks; Model mismatch; Model misspecification; Fake features; Missing features; linear regression; regularization; Machine learning; Maskininlärning;

    Sammanfattning : Machine learning models are typically configured by minimizing the training error over a given training dataset. On the other hand, the main objective is to obtain models that can generalize, i.e., perform well on data unseen during training. LÄS MER

  5. 4. The Quest for Robust Model Selection Methods in Linear Regression

    Författare :Prakash Borpatra Gohain; Magnus Jansson; K.V.S Hari; KTH; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Model selection; information criterion; linear regression; sparsity; high dimensional; Electrical Engineering; Elektro- och systemteknik; Mathematical Statistics; Matematisk statistik;

    Sammanfattning : A fundamental requirement in data analysis is fitting the data to a model that can be used for the purpose of prediction and knowledge discovery. A typical and favored approach is using a linear model that explains the relationship between the response and the independent variables. LÄS MER

  7. 5. Bilinear Regression and Second Order Calibration

    Författare :Marie Linder; Pieter Kroonenberg; Stockholms universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; chemometrics; calibration; multivariate; hyphenated methods; matrix data; bilinear model; least squares; singular value decomposition; generalized rank annihilation; trilinear decomposition; parallel factor analysis; principal components regression; partial least squares; prediction; matematisk statistik; Mathematical Statistics;

    Sammanfattning : We consider calibration of second-order (or "hyphenated") instruments for chemical analysis. Many such instruments generate bilinear two-way (matrix) type data for each specimen. The bilinear regression model is to be estimated from a number of specimens of known composition. LÄS MER