The calibration of transfer functions is essential for accurate pavement performance predictions in the PavementME design. Several studies have used the least square approach to calibrate these transfer functions. Lea...The calibration of transfer functions is essential for accurate pavement performance predictions in the PavementME design. Several studies have used the least square approach to calibrate these transfer functions. Least square is a widely used simplistic approach based on certain assumptions. Literature shows that these least square approach assumptions may not apply to the non-normal distributions. This study introduces a new methodology for calibrating the transverse cracking and international roughness index(IRI) models in rigid pavements using maximum likelihood estimation(MLE). Synthetic data for transverse cracking, with and without variability, are generated to illustrate the applicability of MLE using different known probability distributions(exponential,gamma, log-normal, and negative binomial). The approach uses measured data from the Michigan Department of Transportation's(MDOT) pavement management system(PMS) database for 70 jointed plain concrete pavement(JPCP) sections to calibrate and validate transfer functions. The MLE approach is combined with resampling techniques to improve the robustness of calibration coefficients. The results show that the MLE transverse cracking model using the gamma distribution consistently outperforms the least square for synthetic and observed data. For observed data, MLE estimates of parameters produced lower SSE and bias than least squares(e.g., for the transverse cracking model, the SSE values are 3.98 vs. 4.02, and the bias values are 0.00 and-0.41). Although negative binomial distribution is the most suitable fit for the IRI model for MLE, the least square results are slightly better than MLE. The bias values are-0.312 and 0.000 for the MLE and least square methods. Overall, the findings indicate that MLE is a robust method for calibration, especially for non-normally distributed data such as transverse cracking.展开更多
By exponentiating each of the components of a finite mixture of two exponential components model by a positive parameter, several shapes of hazard rate functions are obtained. Maximum likelihood and Bayes methods, bas...By exponentiating each of the components of a finite mixture of two exponential components model by a positive parameter, several shapes of hazard rate functions are obtained. Maximum likelihood and Bayes methods, based on square error loss function and objective prior, are used to obtain estimators based on balanced square error loss function for the parameters, survival and hazard rate functions of a mixture of two exponentiated exponential components model. Approximate interval estimators of the parameters of the model are obtained.展开更多
In this paper, we consider the construction of the approximate profile-</span><span style="font-family:""> </span><span style="font-family:Verdana;">likelihood confiden...In this paper, we consider the construction of the approximate profile-</span><span style="font-family:""> </span><span style="font-family:Verdana;">likelihood confidence intervals for parameters of the 2-parameter Weibull distribution based on small type-2 censored samples. In previous research works, the traditional Wald method has been used to construct approximate confidence intervals for the 2-parameter Weibull distribution</span><span style="font-family:""> </span><span style="font-family:Verdana;">under type-2 censoring scheme. However, the Wald technique is based on normality assumption and thus may not produce accurate interval estimates for small samples. The profile-likelihood and Wald confidence intervals are constructed for the shape and scale parameters of the 2-parameter Weibull distribution based on simulated and real type-2 censored data, and are hence compared using confidence length and coverage probability.展开更多
Asymptotic results are obtained using an approach based on limit theorem results obtained for α-mixing sequences for the class of general spacings (GSP) methods which include the maximum spacings (MSP) method. The MS...Asymptotic results are obtained using an approach based on limit theorem results obtained for α-mixing sequences for the class of general spacings (GSP) methods which include the maximum spacings (MSP) method. The MSP method has been shown to be very useful for estimating parameters for univariate continuous models with a shift at the origin which are often encountered in loss models of actuarial science and extreme models. The MSP estimators have also been shown to be as efficient as maximum likelihood estimators in general and can be used as an alternative method when ML method might have numerical difficulties for some parametric models. Asymptotic properties are presented in a unified way. Robustness results for estimation and parameter testing results which facilitate the applications of the GSP methods are also included and related to quasi-likelihood results.展开更多
We characterize the hemodynamic response changes near-infrared spectroscopy （NIRS） during the presentation of in the main olfactory bulb （MOB） of anesthetized rats with three different odorants： （i） plain air a...We characterize the hemodynamic response changes near-infrared spectroscopy （NIRS） during the presentation of in the main olfactory bulb （MOB） of anesthetized rats with three different odorants： （i） plain air as a reference （Blank）, （ii） 2-heptanone （HEP）, and （iii） isopropylbenzene （Ib）. Odorants generate different changes in the concentrations of oxy- hemoglobin. Our results suggest that NIRS technology might be useful in discriminating various odorants in a non-invasive manner using animals with a superb olfactory system.展开更多
Maximum likelihood and Bayes estimators of the parameters, survival function (SF) and hazard rate function (HRF) are obtained for the three-parameter exponentiated Burr type XII distribution when sample is available f...Maximum likelihood and Bayes estimators of the parameters, survival function (SF) and hazard rate function (HRF) are obtained for the three-parameter exponentiated Burr type XII distribution when sample is available from type II censored scheme. Bayes estimators have been developed using the standard Bayes and MCMC methods under square error and LINEX loss functions, using informative type of priors for the parameters. Simulation comparison of various estimation methods is made when n = 20, 40, 60 and censored data. The Bayes estimates are found to be, generally, better than the maximum likelihood estimates against the proposed prior, in the sense of having smaller mean square errors. This is found to be true whether the data are complete or censored. Estimates improve by increasing sample size. Analysis is also carried out for real life data.展开更多
提出了一种在Bayes概率统计框架下的混合Bayes超分辨率重建算法,该算法采用Huber马尔可夫随机场(Huber Markov random field,HMRF)模型对理想图像进行先验建模,可以较好地突出重建图像的不连续边缘特征信息。实验结果表明,该算法克服了...提出了一种在Bayes概率统计框架下的混合Bayes超分辨率重建算法,该算法采用Huber马尔可夫随机场(Huber Markov random field,HMRF)模型对理想图像进行先验建模,可以较好地突出重建图像的不连续边缘特征信息。实验结果表明,该算法克服了极大后验概率估计(maximum a posteriori,MAP)算法中的若干缺陷,取得了良好的重建结果,图像边缘特征清晰,纹理信息突出。展开更多
Age and growth characteristics of crimson sea bream Paragyrops edita Tanaka in Beibu Gulf were studied through bottom trawling and gillnet fleets fishing from July 2006 to December 2007. A total number of 1155 individ...Age and growth characteristics of crimson sea bream Paragyrops edita Tanaka in Beibu Gulf were studied through bottom trawling and gillnet fleets fishing from July 2006 to December 2007. A total number of 1155 individuals, ranging from 49 to 249mm in standard length was examined. The age of the fish was determined from sagittal otoliths. One year growth was made up of one translucent and one opaque zone. A maximum likelihood estimation procedure was used to fit the Von Bertalanffy, Logistic and Gompertz growth functions to the length-at-age data. ARSS indicated that there were no significant differences in growth between sexes in the three growth models （P〉0.05）, and the Von Bertalanffy growth function Lr=292.8{1 cxp[-0.167（t＋1.l16）]} was selected as the most appropriate growth model according to Akaike＇s information criterion （AIC）.展开更多
基金the Michigan Department of Transportation (MDOT) for the financial support of this study (report no. SPR1723)。
文摘The calibration of transfer functions is essential for accurate pavement performance predictions in the PavementME design. Several studies have used the least square approach to calibrate these transfer functions. Least square is a widely used simplistic approach based on certain assumptions. Literature shows that these least square approach assumptions may not apply to the non-normal distributions. This study introduces a new methodology for calibrating the transverse cracking and international roughness index(IRI) models in rigid pavements using maximum likelihood estimation(MLE). Synthetic data for transverse cracking, with and without variability, are generated to illustrate the applicability of MLE using different known probability distributions(exponential,gamma, log-normal, and negative binomial). The approach uses measured data from the Michigan Department of Transportation's(MDOT) pavement management system(PMS) database for 70 jointed plain concrete pavement(JPCP) sections to calibrate and validate transfer functions. The MLE approach is combined with resampling techniques to improve the robustness of calibration coefficients. The results show that the MLE transverse cracking model using the gamma distribution consistently outperforms the least square for synthetic and observed data. For observed data, MLE estimates of parameters produced lower SSE and bias than least squares(e.g., for the transverse cracking model, the SSE values are 3.98 vs. 4.02, and the bias values are 0.00 and-0.41). Although negative binomial distribution is the most suitable fit for the IRI model for MLE, the least square results are slightly better than MLE. The bias values are-0.312 and 0.000 for the MLE and least square methods. Overall, the findings indicate that MLE is a robust method for calibration, especially for non-normally distributed data such as transverse cracking.
文摘By exponentiating each of the components of a finite mixture of two exponential components model by a positive parameter, several shapes of hazard rate functions are obtained. Maximum likelihood and Bayes methods, based on square error loss function and objective prior, are used to obtain estimators based on balanced square error loss function for the parameters, survival and hazard rate functions of a mixture of two exponentiated exponential components model. Approximate interval estimators of the parameters of the model are obtained.
文摘In this paper, we consider the construction of the approximate profile-</span><span style="font-family:""> </span><span style="font-family:Verdana;">likelihood confidence intervals for parameters of the 2-parameter Weibull distribution based on small type-2 censored samples. In previous research works, the traditional Wald method has been used to construct approximate confidence intervals for the 2-parameter Weibull distribution</span><span style="font-family:""> </span><span style="font-family:Verdana;">under type-2 censoring scheme. However, the Wald technique is based on normality assumption and thus may not produce accurate interval estimates for small samples. The profile-likelihood and Wald confidence intervals are constructed for the shape and scale parameters of the 2-parameter Weibull distribution based on simulated and real type-2 censored data, and are hence compared using confidence length and coverage probability.
文摘Asymptotic results are obtained using an approach based on limit theorem results obtained for α-mixing sequences for the class of general spacings (GSP) methods which include the maximum spacings (MSP) method. The MSP method has been shown to be very useful for estimating parameters for univariate continuous models with a shift at the origin which are often encountered in loss models of actuarial science and extreme models. The MSP estimators have also been shown to be as efficient as maximum likelihood estimators in general and can be used as an alternative method when ML method might have numerical difficulties for some parametric models. Asymptotic properties are presented in a unified way. Robustness results for estimation and parameter testing results which facilitate the applications of the GSP methods are also included and related to quasi-likelihood results.
基金The MKE(The Ministry of Knowledge Economy),Korea,under the ITRC(Information Technology Research Center)support program supervised by the NIPA(National IT Industry Promotion Agency) (NIPA-2012-H0301-12-2006)Brain Research Center(BRC)(2012K001127),The MKE(10033634-2012-21)National Research Foundation of Korea(NRF)(2012-0005787)
文摘We characterize the hemodynamic response changes near-infrared spectroscopy （NIRS） during the presentation of in the main olfactory bulb （MOB） of anesthetized rats with three different odorants： （i） plain air as a reference （Blank）, （ii） 2-heptanone （HEP）, and （iii） isopropylbenzene （Ib）. Odorants generate different changes in the concentrations of oxy- hemoglobin. Our results suggest that NIRS technology might be useful in discriminating various odorants in a non-invasive manner using animals with a superb olfactory system.
文摘Maximum likelihood and Bayes estimators of the parameters, survival function (SF) and hazard rate function (HRF) are obtained for the three-parameter exponentiated Burr type XII distribution when sample is available from type II censored scheme. Bayes estimators have been developed using the standard Bayes and MCMC methods under square error and LINEX loss functions, using informative type of priors for the parameters. Simulation comparison of various estimation methods is made when n = 20, 40, 60 and censored data. The Bayes estimates are found to be, generally, better than the maximum likelihood estimates against the proposed prior, in the sense of having smaller mean square errors. This is found to be true whether the data are complete or censored. Estimates improve by increasing sample size. Analysis is also carried out for real life data.
文摘提出了一种在Bayes概率统计框架下的混合Bayes超分辨率重建算法,该算法采用Huber马尔可夫随机场(Huber Markov random field,HMRF)模型对理想图像进行先验建模,可以较好地突出重建图像的不连续边缘特征信息。实验结果表明,该算法克服了极大后验概率估计(maximum a posteriori,MAP)算法中的若干缺陷,取得了良好的重建结果,图像边缘特征清晰,纹理信息突出。
基金the National Natural Science Foundation of China (30771653)the program Fish Stock Investigation and Assessment of Beibu Gulf,Ministry of Agriculture,P R China (0509109)
文摘Age and growth characteristics of crimson sea bream Paragyrops edita Tanaka in Beibu Gulf were studied through bottom trawling and gillnet fleets fishing from July 2006 to December 2007. A total number of 1155 individuals, ranging from 49 to 249mm in standard length was examined. The age of the fish was determined from sagittal otoliths. One year growth was made up of one translucent and one opaque zone. A maximum likelihood estimation procedure was used to fit the Von Bertalanffy, Logistic and Gompertz growth functions to the length-at-age data. ARSS indicated that there were no significant differences in growth between sexes in the three growth models （P〉0.05）, and the Von Bertalanffy growth function Lr=292.8{1 cxp[-0.167（t＋1.l16）]} was selected as the most appropriate growth model according to Akaike＇s information criterion （AIC）.
