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Showing 1 to 20 of 25 for “"Akaike Information Criterion (AIC)"”.

  1. Estimating stochastic volatility models with student-t distributed errors

    … to determine the best performing model was the Akaike information criterion (AIC).

    cape-town Repository record for Estimating stochastic volatility models with student-t distributed errors (opens in a new tab)

  2. Minimum description complexity

    … data. The critical task is the choice of a criterion for model set comparison. Pioneer information theoretic based approaches to this problem are Akaike information criterion (AIC) and different forms of minimum description length (MDL). The prior assumption in these methods is that the …

    mit Repository record for Minimum description complexity (opens in a new tab)

  3. Dimensionality reduction in the control of quasi-static force production tasks in humans

    … factorization (NMF) subjected to a generalized Akaike information criterion (AIC) to serve as a quality of fit estimator. These are used to group the muscle activity of individuals during quasi-static force production tasks to synthesize reduced-order models that account for 90\% of the muscle …

    uiuc Repository record for Dimensionality reduction in the control of quasi-static force production tasks in humans (opens in a new tab)

  4. Development of Enhanced Pavement Deterioration Curves

    … deterioration of a pavement section by using the Akaike Information Criterion (AIC). The AIC method suggests that a model that includes the MSI is at least 10^21 times more likely to be closer to the true model than a model that does not include the MSI. The developed models display the average …

    vt Repository record for Development of Enhanced Pavement Deterioration Curves (opens in a new tab)

  5. Parametric survival models with interval censored data in determining prognostic factors of patients of lung cancer

    … and number of sample sizes. Besides, Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Corrected Akaike Information Criterion (AICC) been evaluated in finding the best fit model towards the survival time of lung cancer. Thus, the exponential model was found to …

    uthm Repository record for Parametric survival models with interval censored data in determining prognostic factors of patients of lung cancer (opens in a new tab)

  6. Forecasting the S&P 500 index using time series analysis and simulation methods

    … Mean Square Error (RMSE), Absolute Error (MAE), Akaike information criterion (AIC) and Schwartz Bayesian criterion (SBC). But most importantly, the primary forecasting measure includes MAE and Mean Absolute Percentage Error (MAPE), which uses the forecasted value and the actual S&P 500 level as …

    mit Repository record for Forecasting the S&P 500 index using time series analysis and simulation methods (opens in a new tab)

  7. Performing Network Level Crash Evaluation Using Skid Resistance

    … data used in the study included the following information obtained from Virginia Department of Transportation (VDOT) records: 2010 to 2012 crash data, 2010 to 2012 AADT, and horizontal radius of curvature (CV). Additionally, tire-pavement friction or skid resistance was measured using a …

    vt Repository record for Performing Network Level Crash Evaluation Using Skid Resistance (opens in a new tab)

  8. Application of a New Tree-Ring Based Drought Reconstruction Method at Multiple Forest Sites Across Indiana, U.S.A.

    … root-mean-square error (RMSE), F statistic, and Akaike Information Criterion (AIC). Summer (June–August; JJA) Palmer Drought Severity Index (PDSI) was the best predicated climate variable, thus two separate models (SS and MCOS) were created at each site for reconstruction. The MCOS outperformed …

    usm Repository record for Application of a New Tree-Ring Based Drought Reconstruction Method at Multiple Forest Sites Across Indiana, U.S.A. (opens in a new tab)

  9. Topics In Time Series Analysis And Forecasting

    … of the commonly used selection criteria, Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), are discussed. In the finite case, the study is limited to the two sample problem. The exact probability of selection is obtained for finite samples. The risk of each …

    uwo Repository record for Topics In Time Series Analysis And Forecasting (opens in a new tab)

  10. Complexity analysis of lumped parameter models : development of complexity reduction algorithm

    … varying complexity and the results by using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) as an indicator for model selection have been shown.

    reykjavik Repository record for Complexity analysis of lumped parameter models : development of complexity reduction algorithm (opens in a new tab)

  11. Variants of compound models and their application to citation analysis

    … techniques based on log-likelihood methods, Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The suitability of the models is also assessed using two diagrammatic methods, randomised quantile residual plots and Christmas tree plots. The Christmas tree plots clearly …

    wlv Repository record for Variants of compound models and their application to citation analysis (opens in a new tab)

  12. Cognitive Diagnostic Model, a Simulated-Based Study: Understanding Compensatory Reparameterized Unified Model (CRUM)

    … (CDM) has the potential to provide valuable information for stakeholders to assist students identify their skill deficiency in specific academic subjects. Cognitive diagnosis models are mainly viewed as a family of latent class confirmatory probabilistic models. These models allow the mapping …

    vt Repository record for Cognitive Diagnostic Model, a Simulated-Based Study: Understanding Compensatory Reparameterized Unified Model (CRUM) (opens in a new tab)

  13. Nesting Ecology Of Red-Headed Woodpeckers (Melanerpes Erythrocephalus) In Central Minnesota

    … in dead branches, as supported by lowest Akaike information criterion (AIC) scores among candidate models. Of nests found during the egg laying stage, 100% experienced some amount of brood reduction. On average, nest contents were reduced by 48.1% between egg laying and fledging with …

    umn Repository record for Nesting Ecology Of Red-Headed Woodpeckers (Melanerpes Erythrocephalus) In Central Minnesota (opens in a new tab)

  14. Evaluating Methods for Optimizing Classification Success From Otolith Tracers for Spotted Seatrout (<i>Cynoscion nebulosus</i>) in the Chesapeake Bay

    … of the number of chemical variables used, the information conveyed by each variable, and the overall stability of important variables with time. Almost all studies argue that juvenile signatures must be collected anew each year at considerable expense. In this study, Rao's test for additional …

    odu Repository record for Evaluating Methods for Optimizing Classification Success From Otolith Tracers for Spotted Seatrout (<i>Cynoscion nebulosus</i>) in the Chesapeake Bay (opens in a new tab)

  15. Spatial Infectious Disease Transmission Models: Variable Screening Methods and Logistic Formulation.

    … operator (Lasso), forward and backward stepwise Akaike information criterion (AIC), variable random selection (boosting) methods, spike-and-slab (SS) priors, and two-stage screening methods. These are applied within the context of spatial ILMs with numerous potential susceptible covariates. The …

    calgary Repository record for Spatial Infectious Disease Transmission Models: Variable Screening Methods and Logistic Formulation. (opens in a new tab)

  16. Reducing heart failure admissions through improved care systems and processes

    … significant predictors, as identified by the Akaike information criterion (AIC), include patient's age, marital status, ability to speak English, estimated average income, previous administration of loop diuretics, and the total number of medications prescribed or administered. To assess the …

    mit Repository record for Reducing heart failure admissions through improved care systems and processes (opens in a new tab)

  17. Modeling and Forecasting Ghana's Inflation Rate Under Threshold Models

    … AR(2), were employed and fitted to the data. The Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) were used to assess each of the fitted models such that the model with the minimum value of AIC and BIC, was judged the best model. Additionally, the fitted models were …

    venda Repository record for Modeling and Forecasting Ghana's Inflation Rate Under Threshold Models (opens in a new tab)

  18. Energy Emissions from Critical Phenomena and Applications to Structural Health Monitoring

    … from their critical processes, some useful information or suggestion is extracted and to be provided in structural health monitoring (SHM). Three different forms of energies, acoustic emission (AE), electromagnetic emission (EM) and neutron emission (NE), are selected to be studied in our …

    poli-torino Repository record for Energy Emissions from Critical Phenomena and Applications to Structural Health Monitoring (opens in a new tab)

  19. Multimodal neuroimaging signatures of early cART-treated paediatric HIV - Distinguishing perinatally HIV-infected 7-year-old children from uninfected controls

    … likelihood ratio tests for non-nested models and Akaike information criterion (AIC) for nested models. To identify features most useful in distinguishing HIV infection, the EN model was retrained on all the data, to find features with non-zero weights. Finally, multivariate imputation using …

    cape-town Repository record for Multimodal neuroimaging signatures of early cART-treated paediatric HIV - Distinguishing perinatally HIV-infected 7-year-old children from uninfected controls (opens in a new tab)

  20. Critical study of AIC model selection techniques

    Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2012-01-03T19:52:20Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Tan_MingYangJeremy.pdf: 761560 bytes, checksum: 1ec1ec8cdd591f86a9ba94337abe5c0a (MD5)

    uiuc Repository record for Critical study of AIC model selection techniques (opens in a new tab)

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