Estimating marginal likelihoods for mixture and Markov switching models using bridge sampling techniques

Summary This paper discusses the problem of estimating marginal likelihoods for mixture and Markov switching model. Estimation is based on the method of bridge sampling ( Meng and Wong 1996 ; Statistica Sinica11, 552–86.) where Markov Chain Monte Carlo (MCMC) draws from the posterior density are combined with an i.i.d. sample from an importance density. The importance density is constructed in an unsupervised manner from the MCMC draws using a mixture of complete data posteriors. Whereas the importance sampling estimator as well as the reciprocal importance sampling estimator are sensitive to the tail behaviour of the importance density, we demonstrate that the bridge sampling estimator is far more robust. Our case studies range from computing marginal likelihoods for a mixture of multivariate normal distributions, testing for the inhomogeneity of a discrete time Poisson process, to testing for the presence of Markov switching and order selection in the MSAR model.     

炙甘草合剂中甘草酸含量测定

目的：控制炙甘草合剂的质量。方法：采用高效液相色谱法（HPLC）测定甘草酸的含量。结果：分离度好，含量测定线性范围0．23-1．85μg（r=0．9999），平均回收率96．6％，相对标准差（RSD）0．17％（n=6）。结论：方法简便、准确、重现性好。     

A model for learning to segment temporal sequences, utilizing a mixture of RNN experts together with adaptive variance

This paper proposes a novel learning method for a mixture of recurrent neural network (RNN) experts model, which can acquire the ability to generate desired sequences by dynamically switching between experts. Our method is based on maximum likelihood estimation, using a gradient descent algorithm. This approach is similar to that used in conventional methods; however, we modify the likelihood function by adding a mechanism to alter the variance for each expert. The proposed method is demonstrated to successfully learn Markov chain switching among a set of 9 Lissajous curves, for which the conventional method fails. The learning performance, analyzed in terms of the generalization capability, of the proposed method is also shown to be superior to that of the conventional method. With the addition of a gating network, the proposed method is successfully applied to the learning of sensory–motor flows for a small humanoid robot as a realistic problem of time series prediction and generation.     

疏肝益脾合剂治疗早期肝硬化临床研究

目的：探讨疏肝益脾合剂治疗早期肝硬化的临床效果。方法：将符合标准的42名患者采用随机数字表法随机分为治疗组22例与对照组20例。早期肝硬化患者治疗组口服疏肝益脾合剂,1剂/d,每次300 mL,早、晚服2次,3月为1疗程;对照组口服安络化纤丸,每次6 g,2次/d。3月为1疗程。结果：显效17例,好转4例,无效1例,有效率95.45%;对照组,显效10例,好转3例,无效7例,有效率为65.00%。两组透明质酸酶（HA）、层粘连蛋白（LN）、Ⅲ型前胶原（PCⅢ）及Ⅳ型胶原（IVC）变化结果比较,两组治疗前后门静脉主干内径、脾脏厚度比较,治疗组优于对照组（P〈0.05）。结论：疏肝益脾合剂有保护肝细胞、恢复肝功能、降低转氨酶、抗肝纤维化的作用,对早期肝硬化的治疗疗效显著。     

固本定痫镇痛合剂联合蝎蜈胶囊治疗癫痫临床观察

目的观察固本定痫镇痛合剂联合蝎蜈胶囊治疗癫痫的临床疗效。方法对86例癫痫患者予固本定痫镇痛合剂及蝎蜈胶囊口服;至少观察2个平均发作周期以上,评价癫痫发作次数、发作时症状、持续时间、脑电图的改变、西药添加率及1年中药服用保留率。结果总有效率为66.27%,其中儿童良性中央颞癫痫、单纯部分性发作近期痊愈率较高,分别为52.94%、42.11%;青少年肌阵挛性癫痫、全面性发作有效率低。西药添加率为52.33%,1年中药保留率为80.23%。结论固本定痫镇痛合剂联合蝎蜈胶囊治疗癫痫疗效满意,患者依从性好。     

健脾益气合剂改善抗生素脱污染小鼠肠道菌群失调及细菌易位的实验研究

目的:研究健脾益气合剂对抗生素脱污染小鼠肠道菌群失调的调节作用及其对肠道细菌易位的抑制作用。方法:将40只清洁级小鼠随机分为4组:正常对照组(a组)、模型生理盐水组(b组)、模型丽珠肠乐组(c组)、模型健脾益气合剂组(d组)。除正常对照组外,其他3组均予氨苄青霉素造成肠道菌群失调模型,然后分别给予无菌生理盐水、健脾益气合剂和丽珠肠乐无菌生理盐水稀释液灌胃,每天2次。分别观察各造模组与正常组小鼠粪便变化及体质量变化情况及盲肠、肝脏、肾脏、心脏的组织病理学检查。结果:各组造模成功。治疗后(第11天),b组小鼠仍有60%出现中、重度腹泻,而c,d组小鼠已无中、重度腹泻。b组盲肠组织无明显充血、水肿,仍见炎性细胞浸润,肝实质扩张充血减轻,肝小叶结构欠佳,肝细胞排列拥挤,界限不清,胞浆疏松,未见空泡;而c,d组盲肠组织表面光滑,溃疡面恢复较好,仅见极少量炎性细胞浸润,肝脏未见明显病理学改变。结论:健脾益气合剂对抗生素脱污染小鼠肠道菌群失调有着和丽珠肠乐类似的调节作用,能促进肠黏膜损伤的恢复,抑制肠道细菌易位,使肠道微生态失衡得到调整恢复。     

高效液相色谱法测定麻杏定喘合剂中苦杏仁苷含量

目的探讨测定麻杏定喘合剂中苦杏仁苷含量的方法。方法采用高效液相色谱（HPLC）法,色谱柱为Dikma Kromasil C18柱（250mm×4．6mm,5μm）,流动相为水-甲醇-乙腈（75：20：5）,检测波长为210nm,流速为0．8mL／min,柱温30℃,进样量10μL。结果苦杏仁苷的平均加样回收率为99．02％,RSD=1．37％（n=6）,平均含量为1．3575mg／g。结论所建立的方法操作简便、结果准确,可作为麻杏定喘合剂中苦杏仁苷的含量测定方法。     

Comparative study on pesticide mixture of organophosphorus and pyrethroid in commercial formulation

The marketing of mixtures of organophosphate and pyrethroid insecticides has become very common in developing countries and has resulted in an increase in the prevalence of toxicity. The present study aimed to evaluate the toxic effects of a commercial preparation of the pesticide mixture durasin, which contains 60% diazinon and 0.5% deltamethrin, compared with the individual commercial pesticides of diazinon 30% and deltamethrin 5%. Forty male albino rats weighing 160 ± 20 g were divided into; DA (diazinon 20 mg/Kg b.w.), DA (deltamethrin 2 mg/Kg b.w.), M (durasin 20 mg/Kg b.w.) and control (C); cholinesterase (ChE), malonaldehyde (MDA), glutathione (GSH), glutathione-S-transferase (GST), superoxide dismutase (SOD), total cholesterol (TC), triglyceride (TG) and non-specific esterase's isoenzymes in rat's blood were determined following 7 and 14 days of treatment. The weekly- recorded biochemical results were used as criteria for estimating the joint effects of the tested pesticide mixture. Antioxidant defense mechanisms and lipid peroxidation in rat plasma displayed the same responses with intensities which were related to the different treatments. Biochemical analysis showed that (DA) or (DM) individually cause alteration in lipid metabolism and non-specific esterase, while mixture treatment (M) induced antagonistic effects toward all the tested parameters except total reduced glutathione level, which was synergistic at the 2nd week. In conclusion the commercial mixture (M) under study has potentially greater toxic impact than the components alone in the rat.     

Efficient Calculation of Empirical <Emphasis Type="Italic">P</Emphasis>-values for Genome-Wide Linkage Analysis Through Weighted Permutation

Linkage analysis in multivariate or longitudinal context presents both statistical and computational challenges. The permutation test can be used to avoid some of the statistical challenges, but it substantially adds to the computational burden. Utilizing the distributional dependencies between (defined as the proportion of alleles at a locus that are identical by descent (IBD) for a pairs of relatives, at a given locus) and the permutation test we report a new method of efficient permutation. In summary, the distribution of for a sample of relatives at locus x is estimated as a weighted mixture of drawn from a pool of ‘representative’ distributions observed at other loci. This weighting scheme is then used to sample from the distribution of the permutation tests at the representative loci to obtain an empirical P-value at locus x (which is asymptotically distributed as the permutation test at loci x). This weighted mixture approach greatly reduces the number of permutation tests required for genome-wide scanning, making it suitable for use in multivariate and other computationally intensive linkage analyses. In addition, because the distribution of is a property of the genotypic data for a given sample and is independent of the phenotypic data, the weighting scheme can be applied to any phenotype (or combination of phenotypes) collected from that sample. We demonstrate the validity of this approach through simulation. Edited by David Allison.     

A computer graphical user interface for survival mixture modelling of recurrent infections

Recurrent infections data are commonly encountered in medical research, where the recurrent events are characterised by an acute phase followed by a stable phase after the index episode. Two-component survival mixture models, in both proportional hazards and accelerated failure time settings, are presented as a flexible method of analysing such data. To account for the inherent dependency of the recurrent observations, random effects are incorporated within the conditional hazard function, in the manner of generalised linear mixed models. Assuming a Weibull or log-logistic baseline hazard in both mixture components of the survival mixture model, an EM algorithm is developed for the residual maximum quasi-likelihood estimation of fixed effect and variance component parameters. The methodology is implemented as a graphical user interface coded using Microsoft visual C++. Application to model recurrent urinary tract infections for elderly women is illustrated, where significant individual variations are evident at both acute and stable phases. The survival mixture methodology developed enable practitioners to identify pertinent risk factors affecting the recurrent times and to draw valid conclusions inferred from these correlated and heterogeneous survival data.