Search for dissertations about: "Higher-order statistics"

Showing result 1 - 5 of 34 swedish dissertations containing the words Higher-order statistics.

  2. 1. Algorithmic discovery, development and personalized selection of higher-order drug cocktails : A label-free live-cell imaging & secretomics approach

    Author : Efthymia Chantzi; Mats G Gustafsson; Ulf Hammerling; Andreas Bender; Uppsala universitet; []
    Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; drug combination discovery and development; personalized pharmacotherapy; higher-order drug combination analysis; quantitative label-free live-cell imaging; secretomics; cell-cell communication; deep learning; convolutional neural networks; data mining; MapReduce; resampling; generalized highest single agent; COMBImageDL; COMBSecretomics; Bioinformatics; Bioinformatik; Pharmacology; Farmakologi; Engineering Science; Teknisk fysik;

    Abstract : An upward trend in clinical pharmacology is the use of multiple drugs to combat complex and co-occurring diseases due to better efficacy, decreased toxicity and reduced risk of evolving resistance. Despite high late-stage attrition rates and the need for multi drug treatments, most drug discovery and development efforts are still mainly focused on new one-size-fits-all monotherapies. READ MORE

  4. 2. Approximation of Infinitely Divisible Random Variables with Application to the Simulation of Stochastic Processes

    Author : Magnus Wiktorsson; Matematisk statistik; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; operations research; Statistics; aktuariematematik; Stochastic differential equation; Infinitely divisible distribution; Type G distribution; Lévy process; Stochastic integral; Mathematical Statistics; Matematik; Mathematics; programming; actuarial mathematics; Statistik; operationsanalys; programmering;

    Abstract : This thesis consists of four papers A, B, C and D. Paper A and B treats the simulation of stochastic differential equations (SDEs). The research presented therein was triggered by the fact that there were not any efficient implementations of the higher order methods for simulating SDEs. READ MORE

  5. 3. Neutron monitoring based on the higher order statistics of fission chamber signals

    Author : Zsolt Elter; Chalmers tekniska högskola; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Campbelling mode; Filtered Poisson process; High order; Simulation; Neutron flux monitoring; Experiment; Fission chamber;

    Abstract : The work in this thesis corresponds to the safety aspect of Generation IV nuclear systems. One of the safety aspects concerns the enhancement of the performance of the in-vessel on-line core monitoring with neutron flux measurements. READ MORE

  6. 4. Analysis of regional seismic data by means of higher-order spectra

    Author : Leif Persson; Uppsala universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Earth sciences; Geovetenskap; Earth sciences; Geovetenskap; Geofysik med inriktning mot seismologi; Geophysics with specialization in Seismology;

    Abstract : The use of higher-order statistical and spectral estimators as complementary analysis for conventional regional seismic data processing is studied. The issues addressed are; the properties of the complex bispectrum of regional seismic phases, the experimental detection performance of higher-order statistical detectors, discrimination between local earthquakes and explosions, statistical tests and bicoherence, biphase and spatial bispectrum analysis of regional P-, S, and Lg-phases. READ MORE

  7. 5. Explicit Influence Analysis in Crossover Models

    Author : Chengcheng Hao; Tatjana von Rosen; Dietrich von Rosen; Tapio Nummi; Stockholms universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; explicit maximum likelihood estimate; generalised mixed linear model; influential observation; perturbation scheme; statistical diagnostics; Statistics; statistik;

    Abstract : This dissertation develops influence diagnostics for crossover models. Mixed linear models and generalised mixed linear models are utilised to investigate continuous and count data from crossover studies, respectively. READ MORE