• Title/Summary/Keyword: Akaike Information Criterion

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Abundance Estimation of the Finless Porpoise, Neophocaena phocaenoides, Using Models of the Detection Function in a Line Transect (Line Transect에서 발견율함수 추정에 사용되는 모델에 따른 상괭이, Neophocaena phocaenoides의 자원개체수 추정)

  • Park, Kyum-Joon;Kim, Zang-Geun;Zhang, Chang-Ik
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.40 no.4
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    • pp.201-209
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    • 2007
  • Line transect sampling in a sighting survey is one of most widely used methods for assessing animal abundance. This study applied distance data, collected from three sighting surveys using line transects for finless porpoise that were conducted in 2004 and 2005 off the west coast of Korea, to four models (hazard-rate, uniform, half-normal and exponential) that can use a variety of detection functions, g (x). The hazard-rate model, a derived model for the detection function, should have a shoulder condition chosen using the AIC (Akaike Information Criterion), as the most suitable model. However, it did not describe a shoulder shape for the value of g(x) near the track tine and underestimated g (x), just as the exponential model did. The hazard-rate model showed a bias toward overestimating the densities of finless porpoises with a higher coefficient of variation (CV) than the other models did. The uniform model underestimated the densities of finless porpoise but had the lowest CV. The half-normal model described a detection function with a shape similar to that of the uniform model. The half-normal model was robust for finless porpoise data and should be able to avoid density underestimation. The estimated abundance of finless porpoise was 3,602 individuals (95% CI=1,251-10,371) inshore in 2005 and 33,045 individuals (95% CI=24,274-44,985) offshore in 2004.

Extreme value modeling of structural load effects with non-identical distribution using clustering

  • Zhou, Junyong;Ruan, Xin;Shi, Xuefei;Pan, Chudong
    • Structural Engineering and Mechanics
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    • v.74 no.1
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    • pp.55-67
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    • 2020
  • The common practice to predict the characteristic structural load effects (LEs) in long reference periods is to employ the extreme value theory (EVT) for building limit distributions. However, most applications ignore that LEs are driven by multiple loading events and thus do not have the identical distribution, a prerequisite for EVT. In this study, we propose the composite extreme value modeling approach using clustering to (a) cluster initial blended samples into finite identical distributed subsamples using the finite mixture model, expectation-maximization algorithm, and the Akaike information criterion; (b) combine limit distributions of subsamples into a composite prediction equation using the generalized Pareto distribution based on a joint threshold. The proposed approach was validated both through numerical examples with known solutions and engineering applications of bridge traffic LEs on a long-span bridge. The results indicate that a joint threshold largely benefits the composite extreme value modeling, many appropriate tail approaching models can be used, and the equation form is simply the sum of the weighted models. In numerical examples, the proposed approach using clustering generated accurate extrema prediction of any reference period compared with the known solutions, whereas the common practice of employing EVT without clustering on the mixture data showed large deviations. Real-world bridge traffic LEs are driven by multi-events and present multipeak distributions, and the proposed approach is more capable of capturing the tendency of tailed LEs than the conventional approach. The proposed approach is expected to have wide applications to general problems such as samples that are driven by multiple events and that do not have the identical distribution.

Comparison of Temperature Indexes for the Impact Assessment of Heat Stress on Heat-Related Mortality

  • Kim, Young-Min;Kim, So-Yeon;Cheong, Hae-Kwan;Kim, Eun-Hye
    • Environmental Analysis Health and Toxicology
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    • v.26
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    • pp.9.1-9.9
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    • 2011
  • Objectives: In order to evaluate which temperature index is the best predictor for the health impact assessment of heat stress in Korea, several indexes were compared. Methods: We adopted temperature, perceived temperature (PT), and apparent temperature (AT), as a heat stress index, and changes in the risk of death for Seoul and Daegu were estimated with $^1{\circ}C$ increases in those temperature indexes using generalized additive model (GAM) adjusted for the non-temperature related factors: time trends, seasonality, and air pollution. The estimated excess mortality and Akaike's Information Criterion (AIC) due to the increased temperature indexes for the $75^{th}$ percentile in the summers from 2001 to 2008 were compared and analyzed to define the best predictor. Results: For Seoul, all-cause mortality presented the highest percent increase (2.99% [95% CI, 2.43 to 3.54%]) in maximum temperature while AIC showed the lowest value when the all-cause daily death counts were fitted with the maximum PT for the $75^{th}$ percentile of summer. For Daegu, all-cause mortality presented the greatest percent increase (3.52% [95% CI, 2.23 to 4.80%]) in minimum temperature and AIC showed the lowest value in maximum temperature. No lag effect was found in the association between temperature and mortality for Seoul, whereas for Daegu one-day lag effect was noted. Conclusions: There was no one temperature measure that was superior to the others in summer. To adopt an appropriate temperature index, regional meteorological characteristics and the disease status of population should be considered.

Validity and Reliability of the Korean Version of Person-Centered Practice Inventory-Staff for Nurses (간호사 대상 한국어판 인간중심돌봄 측정도구의 타당도와 신뢰도)

  • Kim, Sohyun;Tak, Sunghee H
    • Journal of Korean Academy of Nursing
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    • v.51 no.3
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    • pp.363-379
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    • 2021
  • Purpose: The purpose of this study was to evaluate the validity and reliability of the Korean version of Person-Centered Practice Inventory-Staff (PCPI-S) for nurses. Methods: The English PCPI-S was translated into Korean with forward and backward translation. Data were collected from 338 nurses at one general hospital in Korea. Construct validity was evaluated with confirmatory factor analysis, convergent validity, and discriminant validity. Known-group validity was also evaluated. Cronbach's α was used to assess the reliability. Results: The PCPI-S Korean version consisted of 51 items in three areas: prerequisites, the care environment, and person-centered process. The comparative fit index (CFI) and values of person-centered care process were improved after engagement and having sympathetic presence items were combined as one component. The construct validity of PCPI-S Korean version was verified using four-factor structures (.05 < RMSEA < .10, AGFI > .70, CFI > .70, and AIC). The convergent validity and discriminant validity of the entire PCPI-S question were verified using a two-factor structures (AVE > .50, construct reliability > .70). There was an acceptable known-group validity with a significant correlation between the PCPI-S level and the degree of person-centered care awareness and education. Internal consistency was reliable with Cronbach's α .95. Conclusion: The Korean version of PCPI-S is valid and reliable. It can be used as a standardized Korean version of person-centered care measurement tool. Abbreviation: RMSEA = root mean square error of approximation; AGFI = adjusted goodness of fit index; AIC = Akaike information criterion; AVE = average variance extracted.

Novel nomogram-based integrated gonadotropin therapy individualization in in vitro fertilization/intracytoplasmic sperm injection: A modeling approach

  • Ebid, Abdel Hameed IM;Motaleb, Sara M Abdel;Mostafa, Mahmoud I;Soliman, Mahmoud MA
    • Clinical and Experimental Reproductive Medicine
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    • v.48 no.2
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    • pp.163-173
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    • 2021
  • Objective: This study aimed to characterize a validated model for predicting oocyte retrieval in controlled ovarian stimulation (COS) and to construct model-based nomograms for assistance in clinical decision-making regarding the gonadotropin protocol and dose. Methods: This observational, retrospective, cohort study included 636 women with primary unexplained infertility and a normal menstrual cycle who were attempting assisted reproductive therapy for the first time. The enrolled women were split into an index group (n=497) for model building and a validation group (n=139). The primary outcome was absolute oocyte count. The dose-response relationship was tested using modified Poisson, negative binomial, hybrid Poisson-Emax, and linear models. The validation group was similarly analyzed, and its results were compared to that of the index group. Results: The Poisson model with the log-link function demonstrated superior predictive performance and precision (Akaike information criterion, 2,704; λ=8.27; relative standard error (λ)=2.02%). The covariate analysis included women's age (p<0.001), antral follicle count (p<0.001), basal follicle-stimulating hormone level (p<0.001), gonadotropin dose (p=0.042), and protocol type (p=0.002 and p<0.001 for short and antagonist protocols, respectively). The estimates from 500 bootstrap samples were close to those of the original model. The validation group showed model assessment metrics comparable to the index model. Based on the fitted model, a static nomogram was built to improve visualization. In addition, a dynamic electronic tool was created for convenience of use. Conclusion: Based on our validated model, nomograms were constructed to help clinicians individualize the stimulation protocol and gonadotropin doses in COS cycles.

Analysis of Success and Failure Factors of OTT Service Contents According to the Rating: Focus on Netflix (평점에 따른 OTT 서비스 콘텐츠의 성공과 실패 요인 분석: 넷플릭스를 중심으로)

  • Hong, Ji-Soo;Park, Jin-Soo;Kang, Sung-Woo
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.44 no.4
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    • pp.65-75
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    • 2021
  • This study explores multiple variables of an OTT service for discovering hidden relationship between rating and the other variables of each successful and failed content, respectively. In order to extract key variables that are strongly correlated to the rating across the contents, this work analyzes 170 Netflix original dramas and 419 movies. These contents are classified as success and failure by using the rating site IMDb, respectively. The correlation between the contents, which are classified via rating, and variables such as violence, lewdness and running time are analyzed to determine whether a certain variable appears or not in each successful and failure content. This study employs a regression analysis to discover correlations across the variables as a main analysis method. Since the correlation between independent variables should be low, check multicollinearity and select the variable. Cook's distance is used to detect and remove outliers. To improve the accuracy of the model, a variable selection based on AIC(Akaike Information Criterion) is performed. Finally, the basic assumptions of regression analysis are identified by residual diagnosis and Dubin Watson test. According to the whole analysis process, it is concluded that the more director awards exist and the less immatatable tend to be successful in movies. On the contrary, lower fear tend to be failure in movies. In case of dramas, there are close correlations between failure dramas and lower violence, higher fear, higher drugs.

The change of rainfall quantiles calculated with artificial neural network model from RCP4.5 climate change scenario (RCP4.5 기후변화 시나리오와 인공신경망을 이용한 우리나라 확률강우량의 변화)

  • Lee, Joohyung;Heo, Jun-Haeng;Kim, Gi Joo;Kim, Young-Oh
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.130-130
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    • 2022
  • 기후변화로 인한 기상이변 현상으로 폭우와 홍수 등 수문학적 극치 사상의 출현 빈도가 잦아지고 있다. 따라서 이러한 기상이변 현상에 적응하기 위하여 보다 정확한 확률강우량 측정의 필요성이 증가하고 있다. 대장 지점의 미래 확률강우량 계산을 위해선 기후변화 시나리오의 비정상성을 고려해야 한다. 본 연구는 비정상적인 미래 기후에서 확률강우량이 어떻게 변화하는지 측정하는 것을 목표로 한다. Representative Concentration Pathway (RCP4.5)에 따른 우리나라의 확률강우량 계산에 인공신경망을 포함한 정상성, 비정상성 확률강우량 산정 모델들이 사용되었다. 지점빈도해석(AFA), 홍수지수법(IFM), 모분포홍수지수법(PIF), 인공신경망을 이용한 Quantile & Parameter regression technique(QRT & PRT)이 정상성 자료에 대해 확률강우량을 계산하는 모델로 사용되었으며, 비정상성 자료에 대해서는 비정상성 지점빈도해석(NS-AFA), 비정상성 홍수지수법(NS-IFM), 비정상성 모분포홍수지수법(NS-PIF), 인공신경망을 사용한 비정상성 Quantile & Parameter regression technique(NS-QRT & NS-PRT)이 사용되었다. Rescaled Akaike information criterion(rAIC)를 사용한 불확실성 분석과 적합도 검정을 통해서 generalized extreme value(GEV) 분포형 모델이 정상성 및 비정상성 확률강우량 산정에 가장 적합한 모델로 선정되었다. 이후, 관측자료가 GEV(0,0,0)을 따르고 시나리오 자료가 GEV(1,0,0)을 따르는 지점들을 선택하여 미래의 확률강우량 변화를 추정하였다. 각 빈도해석 모델들은 몬테카를로 시뮬레이션을 통해 bias, relative bias(Rbias), root mean square error(RMSE), relative root mean square error(RRMSE)를 바탕으로 측정하여 정확도를 계산하였으며 그 결과 QRT와 NS-QRT가 각각 정상성과 비정상성 자료로부터 가장 정확하게 확률강우량을 계산하였다. 본 연구를 통해 향후 기후변화의 영향으로 확률강우량이 증가할 것으로 예상되며, 비정상성을 고려한 빈도분석 또한 필요함을 제안하였다.

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Evaluation of Megasphaera elsdenii supplementation on rumen fermentation, production performance, carcass traits and health of ruminants: a meta-analysis

  • Irwan Susanto;Komang G. Wiryawan;Sri Suharti;Yuli Retnani;Rika Zahera;Anuraga Jayanegara
    • Animal Bioscience
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    • v.36 no.6
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    • pp.879-890
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    • 2023
  • Objective: This study was conducted to evaluate the use of Megasphaera elsdenii (M. elsdenii) as a probiotic on rumen fermentation, production performance, carcass traits and health of ruminants by integrating data from various related studies using meta-analysis. Methods: A total of 32 studies (consisted of 136 data points) were obtained and integrated into a database. The parameters integrated were fermentation products, rumen microbes, production performance, carcass quality, animal health, blood and urine metabolites. Statistical analysis of the compiled database used a mixed model methodology. Different studies were considered random effects, while M. elsdenii supplementation doses were considered fixed effects. p-values and the Akaike information criterion were employed as model statistics. The model was deemed significant at p<0.05 or had a tendency to be significant when p-value between 0.05<p<0.10. Results: Supplementation with M. elsdenii increased (p<0.05) some proportion of fermented rumen products such as propionate, butyrate, isobutyrate, and valerate, and significantly reduced (p<0.05) lactic acid concentration, acetate proportion, total bacterial population and methane emission. Furthermore, the probiotic supplementation enhanced (p<0.05) livestock production performance, especially in the average daily gain and body condition score. Regarding the carcass quality, hot carcass weight and carcass gain were elevated (p< 0.05) due to the M. elsdenii supplementation. Animal health also showed improvement as indicated by the lower (p<0.05) diarrhoea and bloat incidences as well as the liver abscess. However, M. elsdenii supplementation had negligible effects on blood and urine metabolites of ruminants. Conclusion: Supplementation of M. elsdenii is capable of decreasing ruminal lactic acid concentration, enhancing rumen health, elevating some favourable rumen fermentation products, and in turn, increasing production performance of ruminants.

Application of Nonstatinoary Regional Frequency Analysis Based on Population Index Flood Model (모분포 홍수지수모형을 이용한 비정상성 지역빈도해석 기법 적용)

  • Kim, Hanbeen;Lee, Joohyung;Park, Jaeheyon;Heo, Jun-Haeng
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.98-98
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    • 2020
  • 모분포 홍수지수모형은 여러 관측지점의 수문자료를 활용하여 설계수문량을 산정하는 지역빈도해석을 위한 모형 중 하나이다. 기존의 홍수지수모형은 동질지역 내 각 지점의 표본통계량을 통해 표준화된 자료들을 기반으로 설계수문량을 산정하므로 왜곡이나 오차가 발생하는 반면, 모분포 홍수지수모형은 미지의 모분포에 대한 통계량으로 표준화한 설계수문량은 동질지역 내 모든 지점에 대해 동일하다는 가정을 기반으로 지역빈도해석을 수행하므로 보다 정확한 설계수문량 산정이 가능하다. 본 연구에서는 모분포 홍수지수모형에서의 미지의 모분포를 비정상성 GEV분포형으로 가정함으로써 각 지점의 비정상성을 고려한 설계수문량을 산정할 수 있는 비정상성 지역빈도해석 기법을 개발하고 그 적용성을 알아보고자 한다. 이를 위해 우리나라 전역에 분포된 10개의 강우관측 지점을 하나의 지역으로 구성하고 이질성척도를 통해 지역동질성을 확인하였다. 먼저, 각 지점의 모분포를 가정하기 위하여 각 지점의 연 최대치 강우자료에 대하여 Mann-Kendall test를 통해 경향성을 확인하였다. 경향성이 없는 지점의 경우 정상성 GEV분포형, 경향성이 나타나는 지점의 경우 다양한 형태의 비정상성 GEV분포형 중 Akaike information criterion을 통해 선정된 비정상성 GEV분포형을 모분포로 가정하고, 모분포 홍수지수모형을 적용하여 확률강우량을 산정하였다. 대상 지역에 대한 모의실험을 통해 비정상성을 고려한 모분포 홍수지수모형의 성능을 지점빈도해석 및 기존의 홍수지수모형과 비교하였으며, 정상성 지역빈도해석 대비 비정상성 지역빈도해석을 통해 산정된 확률강우량의 비교를 통해 그 적용성을 평가하였다.

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Evaluation of models for estimation of genetic parameters for post-weaning body measurements and their association with yearling weight in Nellore sheep

  • Satish Kumar Illa;Gangaraju Gollamoori;Sapna Nath
    • Animal Bioscience
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    • v.37 no.3
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    • pp.419-427
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    • 2024
  • Objective: The objective of this study was to obtain (co) variance components and genetic parameter estimates for post-weaning body measurements such as body length (BL), height at withers (HW), and chest girth (HG) recorded at six (SBL, SHW, and SHG), nine (NBL, NHW, and NHG) and twelve (YBL, YHW, and YHG) months of age along with yearling weight (YW) in Nellore sheep maintained at livestock research station, Palamaner, Andhra Pradesh, India and also the association among body measurements with YW was studied. Methods: Data on 2,076 Nellore sheep (descended from 75 sires and 522 dams) recorded between 2007 and 2016 (10 years) were utilized in the study. Lambing year, sex of lamb, season of lambing and parity of dam were included in the model as fixed effects and ewe weight was kept as a covariate. Analyses were conducted with six animal models with different combinations of direct and maternal genetic effects using restricted maximum likelihood procedure. Best model for each trait was determined based on Akaike's information criterion. Results: Moderate estimates of direct heritability were obtained for the studied traits viz., BL (0.02 to 0.24), HW (0.31 to 0.49), and CG (0.08 to 0.35) and their corresponding maternal heritability estimates were in the range of 0.00 to 0.07 (BL), 0.13 to 0.17 (HW), and 0.07 to 0.13 (CG), respectively. Positive direct genetic and phenotypic correlations among the traits and they ranged from 0.07 (YBL-YW) to 0.99 (SBL-SHG, SHG-YW, and NBL-YBL) and 0.01 (SBL-YBL) to 0.99 (NBL-NHG), respectively. Further, the genetic correlations among all the body measurements and YW were positive and ranged from 0.07 (YW and YBL) to 0.99 (YW and SHG). Conclusion: There was a strong association of chest girth at six months with YW. Further, it is indicated that moderate improvement of post-weaning body measurements in Nellore sheep would be possible through selection.