Model Selection Sample Clauses

Model Selection. In order to compare our dynamic latent trait model with the benchmark model we use the deviance information criterion (DIC; according to Xxxxxxxxxxxxx et al., 2002). The DIC is a generalization of the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) for hierarchical models. In contrast to the AIC and BIC, DIC allows to compare Bayesian hierarchical models where the effective number of parame- ters is not clearly defined. Similar to the other information criteria a trade-off between model fit and model complexity is evaluated. The DIC contains one penalty term for the effective number of parameters used measuring model complexity and one term equal to the deviance of the likelihood measuring model fit. A lower DIC value indicates a better model fit. According to Xxxxxxxxxxxxx et al. (2002), if the difference in DIC is greater than 10, then the model with the larger DIC value has considerably less support than the model with the lower DIC value. For our models, the lower DIC value of our dynamic latent trait model (DIC = 9485.77) indicates that this model dominates in the terms of model fit as well as model complexity the obvious benchmark model (DIC = 12319.82). Rating errors. We begin our analysis of the estimation results with the rating errors. Our dynamic latent trait model captures estimates for the rating bias µj and the standard deviation σj of the rating error of the big three external rating agencies on the score scale. Table 3.8 shows the results for the estimated posterior distribution of the parameters for the three raters µj and σj, respectively. The posterior distributions of the parameters are characterized by the mean values (mean) and the standard deviations (SD) of the 18, 000 (4 × 4, 500) posterior draws. We infer from Table 3.8 that Fitch has the smallest absolute rating bias from µj σj mean SD mean SD Fitch 0.0155 0.0018 0.0752 0.0021 Moody’s 0.0887 0.0024 0.1013 0.0029 S&P 0.0732 0.0017 0.0641 0.0017 Table 3.8: Estimated rating bias µj and standard deviations σj for the rat- ing errors (on the score scale) of the big three external rating agencies Fitch, Moody’s and Standard&Poor’s. The posterior distributions of the parame- ters are characterized by the mean values (mean) and the standard deviations (SD) of the 18, 000 (4 × 4, 500) posterior draws. the consensus on the score scale with respect to the posterior mean (0.0155). Moody’s clearly seems to be too optimistic in its credit assessment yielding a p...
AutoNDA by SimpleDocs
Model Selection. The Fifth-Generation NCAR / Penn State Mesoscale Model Version 3.7 (MM5; Xxxxx et al. 1994) and the NCAR Advanced Research Weather Research and Forecasting Model Version 3 (WRF; Xxxxxxxxx et al. 2008) were selected as the two meteorological models to be implemented in the upgraded PATH modelling system. Preprocessor programs of the MM5 modelling system including terrain, REGRID, LITTLE_R, and INTERPF were used to develop model inputs.
Model Selection. Using backwards elimination with a significance level of 0.10, the linear regression model for keratometric astigmatism at 1 year of age did not give any significant variables among surgical factors. Using the change variables, two surgical factors were given in the stepwise regression model: individual number of sutures (p = 0.061) and incision location (p = 0.071). The model is then: Δ K-Ast = 11.971 – 0.818 (Incision Loc.) – 0.830 (# Sutures). A mixed model with subject-specific intercepts containing all potential surgical factors of interest gave no significant results. The mixed model was given as: Ŷij = αi + bij tij + 0.213 X1 – 0.014 X2 + 0.061 X3 + 0.20 X4 – 0.14 X5 + 0.010 tij, where: Ŷij = Keratometric astigmatism in patient i at visit j; αi = Subject specific random effect on the intercept for subject i; bij = Subject specific random effect on the slope; X1 = Incision Type: 1 for Scleral Tunnel, 0 for Clear Corneal; X2 = Incision Location; X3 = Extended Keratome: 1 for Yes, 0 for No; X4 = Number of Sutures; X5 = Suture Type: 1 for Running, 0 for Interrupted; tij = Age of patient i at visit j, given in months. The lowest p-value of these variables was number of sutures (p = 0.190). The age variable in this model was also non-significant (p = 0.574). In the context of the model, all surgical factors are considered fixed effects, while age at surgery is treated as both a fixed and a random (subject-specific) effect.
Model Selection. A logistic mixed effects model was used to investigate potential relationships between a binary outcome variable, i.e. the presence of a hitchhiker species with a group of explanatory variables such as manta ray gender. The model contained a random intercept to account for the correlation arising from individual mantas being repeatedly observed. To compare the goodness-of-fit, a GLMM model without random effects was tested. To ensure sufficient credibility to reliably estimate the parameters, categories of variables with cell counts below five were combined or removed such as injury type and breaching behaviour. The category ‘fresh mating wound’ from the pregnancy status variable was not included, since it was not possible to determine pregnancy status. The full model included the explanatory variables: manta ray gender, maturity status, pregnancy status, behavioural activity and sub-region (location of sighting). The Akaike information criterion (AIC) was used for the model selection procedure to determine the most important variables to include in the model. A lower AIC between two candidate models implies an improved fit to the data. The model was run separately for each of the hitchhiker species, and all of the variable combinations were tested (S2 Appendix, Tables 1-5). Next, the parameters (explanatory variables) with the lowest AIC were interpreted on the log odds scale (exp(parameter)) to obtain odds ratio values. The significance of each parameter was determined by whether the 95% confidence interval (CI) crossed one (non-significant). A narrow CI indicated that the estimate was known more precisely, in comparison to a wider CI which had a greater uncertainty. The analysis was performed using RStudio version 1.3.1056 [35].
Model Selection. Table 4. Unadjusted and adjusted odds ratios of various characteristics with antenatal care adequacy Reproductive Age Women (15-49 years old) Receiving At Least One Prenatal Care Visit North and South Kivu (MICS 2010)
Model Selection. A set of 13 models was fit to the data to examine the importance of year-specific apparent survival (S), reach transition probabilities (ψ, probability of a fish moving from Black Rocks to Westwater, and vice versa), and p’s (Table 1). The modeling strategy was a typical one where best estimates of p’s for increasingly complex models were estimated and followed by addition of other parameters (see Xxxxxxx et al. 2010 or more details). The top model in the set contained 45% of the AICc weight and had 70 estimable parameters including survival rates for each reach and year and as a function of TL and TL2, transition probabilities, and probabilities of capture for every year, reach, and state combination. The second-ranked model had 35% of total model weight and one fewer parameter (the TL2 term), with all else being the same. Because the signs of the survival terms in the top and second-ranked models were the same and those models contained the bulk of the total weight (80%), and presented essentially the same trends, only the top-ranked model was interpreted in this analysis. A model with year and reach specific survival rates (94 total parameters, model 11 in the set) received no weight and many survival parameters were not estimable. Annual abundance estimates for adult Humpback Chub (>200 mm TL) were calculated for 1998- 2012 using the Xxxxxxx estimator in the robust design model in Program MARK. The annual abundance estimates for Humpback Chub ranged from 1,139 (2008) to 6,747 (1998; Figure 2). Point estimates 95% confidence intervals (CI) for 1998–2000 were: 6,747 (4,001–11,636), 3,520 (2,513–4,979), and 2,266 (1,742–2,975), respectively. Point estimates for 2003–2005 were: 2,520 (1,814–3,554), 2,724 (2,034–3,689), and 2,000 (1,596–2,530), respectively. Point estimates for 2007–2008 were: 1,212 (972–1,532) and 1,139 (954–1,379), respectively. Point estimates for 2011–2012 were: 1,467 (1,175–1,861) and 1,315 (1,022–1,713), respectively (Figure 2). Significance of differences in estimates was tested based on over lapping confidence intervals (Schenker and Gentleman 2001). The last four years (2007, 2008, 2011, and 2012) were significantly (p<0.05) lower than the previous six years sampled (1998, 1999, 2000, 2003, 2004, and 2005) except for 2000, 2003, and 2005. Abundance estimates for juvenile Humpback Chub and first year adult Humpback Chub (200– 220 mm TL) were not attempted due to the low numbers of these size classes collected throughout all study ye...
Model Selection. No major multicollinearity problems were detected for this initial logistic regression model. Two-way interaction was considered for prior antibiotic use by race and AGE contact outside the household, however, a likelihood ratio test for the interaction terms showed no statistically significant interaction (X2df=1=0.018, p=0.89). Since the interaction terms were found not to be statistically significant they were eliminated from the model. Assessment of confounding using the 10% change in estimate approach revealed no meaningful confounding by race or contact with an AGE affected person outside the household as all model subsets had an adjusted odds ratio within 10% of the full model (gold standard) (Supplemental Table 1). Precision of the odds ratio estimates was also considered and there was no meaningful gain in precision comparing the full model (CI ratio= 3.2) to the model with only prior antibiotic use (CI ratio=3.0) (Supplemental Table 1). Since there was little loss in precision when controlling for these variables it was decided that the model containing race and contact with an AGE affected person outside the household would be considered as the final model for norovirus-associated AGE. The model was found to have good fit with a deviance statistic of 3.58 and a p-value of
AutoNDA by SimpleDocs
Model Selection. The Delft3D suite of models will be utilized to provide a modelling platform for hydrodynamic and water quality modelling. A Delft3D model (“WHCW model”) covering marine waters of at least 7 km from the Project boundary has been developed in a previous preliminary study (1) (referred as the Feasibility Study hereafter) for developing the proposed CMPs. The WHCW model was developed based on the Update Model developed under the Update on Cumulative Water Quality and Hydrological
Model Selection 

Related to Model Selection

  • Panel Selection 1. The Parties shall apply the following procedures in selecting a Panel: (a) the Panel shall comprise 3 members; (b) within 15 days following the date of the establishment of the Panel, each Party shall nominate a Panelist; (c) the Parties shall endeavor 2. If a Panelist appointed under this Article resigns or becomes unable to act, a successor Panelist shall be appointed within 30 days in accordance with the selection procedure as prescribed for the appointment of the original Panelist and the successor shall have all the powers and duties of the original Panelist. The work of the Panel shall be suspended during the appointment of the successor Panelist.

  • Shift Selection Employee assignments within the Patrol Bureau will occur between approximately April 1-15 and shall be awarded based upon seniority. Approximately three (3) months before then the Department will publish a call for written requests on shift assignment. Employees will make their first three (3) choices known. Employees will learn of the assignment, including days off associated with their assignment, immediately after the bidding process is completed. Assignments will take effect on the schedule immediately following July 1st. Residence Hall assignments will be made prior to all others. No officer will be required to work a Residence Hall assignment in consecutive years. Assignment of the remaining officers will begin with selection(s) for day and night shifts. The bid for assignments will continue until all positions are filled. The following general rules apply to assignments: 1. During the term of this Agreement, no employee will be reassigned to a different shift other than the shift awarded by seniority except in situations where the University cannot continue to provide police services. In the event a shift reassignment must occur, it will be offered to volunteers based on seniority. If there are no volunteers it will be assigned to the least senior officer in the department. 2. Shift selection shall be an appropriate subject for the Joint Labor/Management Committee. 3. If a shift becomes available as a result of trainees being released for duty, and if there is at least four (4) months until the next shift change, the shift will be posted and awarded by seniority. The new trainee released for duty will take the senior officers shift. If no employee desires the shift, the trainee scheduled for assignment will be assigned that shift. The parties recognize that for the betterment of the Department it may be necessary to assign a trainee to a specific shift. 4. Voluntary shift trades will be allowed as long as overtime costs are not incurred. 5. Except in a bona fide emergency, no employee shall be assigned to work more than sixteen (16) hours in a twenty-four (24) hour period, provided however employees may volunteer to work up to eighteen (18) hours in a twenty-four (24) hour period.

  • Site Selection 5.1.1 If the parties have not designated the street address of the Franchised Location on Exhibit A on the Effective Date, Franchisee shall identify, submit and obtain Franchisor’s prior written approval of the Franchised Location meeting the requirements of this Agreement prior to entering a lease or sublease for the Franchised Location. Franchisee shall provide Franchisor all information required by Franchisor, as determined by Franchisor in Franchisor’s sole determination, necessary for Franchisor to evaluate the Franchised Location. Franchisor shall have ten (10) business days to review Franchisee’s written site proposal for the Franchised Location and notify Franchisee of its approval or disapproval in writing. Franchisor’s failure to respond within ten (10) business days shall signify Franchisor’s disapproval of the site. Franchisor shall not unreasonably withhold Franchisor’s approval of a proposed site for the Franchised Location. 5.1.2 Franchisee must have a site for the Franchised Location approved by Franchisor, receive the opening notice from Franchisor described in Section 5.4 below, and open Franchisee’s Franchised Business for business within six (6) months from the Effective Date, except as otherwise provided in Section 5.1.3 All matters related in any way to Franchisee’s site are Franchisee’s sole responsibility, regardless of any assistance Franchisor may choose to provide. Franchisee is responsible for obtaining any architectural and engineering services required for Franchisee’s facility and for ensuring its compliance with local law. Neither Franchisor, nor any other person or company associated with Franchisor shall have any liability for any site‐related matter. Xxxxxxxxxx agrees not to make any claims against Franchisor and/or any of Franchisor’s affiliates or associates with regard to such matters. 5.1.4 If Franchisor makes a loan to Franchisee for (i) Franchisee’s purchase of the franchise for the Franchised Business; (ii) the remodeling of the Franchised Location; (iii) the transfer of any interest in this franchise or this Agreement; or (iv) any other purpose; Franchisee shall open (or re‐open, as the case may be), the Franchised Business for business within sixty (60) days from the loan origination date.

  • Single Source Selection Services for tasks in circumstances which meet the requirements of paragraph 3.10 of the Consultant Guidelines for Single Source Selection, may, with the Association's prior agreement, be procured in accordance with the provisions of paragraphs 3.9 through 3.13 of the Consultant Guidelines.

  • Adverse Selection No selection procedures adverse to the Noteholders were utilized in selecting the Receivables from those receivables owned by AmeriCredit which met the selection criteria set forth in clauses (A) through (M) of number 29 of this Schedule B.

  • Least-cost Selection Services for assignments which the Association agrees meet the requirements of paragraph 3.6 of the Consultant Guidelines may be procured under contracts awarded on the basis of Least-cost Selection in accordance with the provisions of paragraphs 3.1 and 3.6 of the Consultant Guidelines.

  • Mortgagor Selection No Mortgagor was encouraged or required to select a Mortgage Loan product offered by the Originator which is a higher cost product designed for less creditworthy mortgagors, unless at the time of the Mortgage Loan's origination, such Mortgagor did not qualify taking into account credit history and debt-to-income ratios for a lower-cost credit product then offered by the Originator or any Affiliate of the Originator. If, at the time of loan application, the Mortgagor may have qualified for a lower-cost credit product then offered by any mortgage lending Affiliate of the Originator, the Originator referred the related Mortgagor's application to such Affiliate for underwriting consideration;

  • Vacation Selection Employees who have not selected their vacation periods by November 15th shall not be entitled later to select vacation periods by seniority. Employees who do not select all of their vacation entitlements on the calendar shall be allowed to schedule vacation at a later date, provided that this selection does not affect the scheduled vacations of other employees.

  • Personnel Selection Leave 35.6.1 Where an employee participates in a personnel selection process for a position in the Public Service, as defined in the Financial Administration Act, the Council shall grant leave of absence with pay for the period during which the employee's presence is required for purposes of the selection process, and for such further period as the Council considers reasonable for the employee to travel to and from the place where his presence is so required.

  • Preference for domestically manufactured goods The provisions of paragraphs 2.54 and 2.55 of the Guidelines and Appendix 2 thereto shall apply to goods manufactured in the territory of the Borrower.

Draft better contracts in just 5 minutes Get the weekly Law Insider newsletter packed with expert videos, webinars, ebooks, and more!