简介:陆地use/陆地盖子变化的转变由于人的数字和活动发生。因为它帮助理解陆地使用的机制变化并且因此帮助做的相关政策,当模特儿的城市的生长吸引了实质的注意。这份报纸趋于使用逻辑回归在湖北省的Jiayu县为城市的生长建模,中国。计算变量在GIS环境被使用并且,然后在社会科学统计套装软体到发现在城市的生长和驱动力之间的关系。相对操作特征(巨鸟)与曲线显示出当模特儿的精确性0.891与标准错误0.001。一张概率地图最后被产生预言城市的生长在哪儿将由于计算发生。结果证明模型在县规模模仿城市的生长很好。
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简介:山崩危险性地图是描绘未来斜坡失败危险性的空间分发的学习地之一。这篇论文为生产山崩危险性地图处理过去的方法;把这些方法划分成3种类型。逻辑线性回归途径进一步被详细描述在上由交叉表方法,它被用来分析在范畴或二进制的反应变量之间的关系;至少一个连续或范畴或二进制的解释变量源于样品。它是当专家意见在启发式的途径有大差别时,在考虑下面用作各种各样的因素的重量的系数的一项客观任务。与确定的途径不同,它对地区性的规模很适用。在这研究,两倍逻辑回归在学习区域被使用。全部学习区域首先被分析。逻辑回归方程显示出那举起,最近到道路,河;居住区域是在这个区域触发山崩出现的主要因素。第一张山崩危险性地图的预言精确性被显示是80%。沿着道路;居住区域,几乎所有区域在高山崩危险性地区。一些非山崩区域不正确地被划分成高度;中等山崩危险性地区。以便改进地位,第二逻辑回归用山崩房间在高山崩危险性地区被做;在这个区域的非山崩样品房间。在第二逻辑回归分析,仅仅设计;地质的条件在这些区域是重要的;在显示那的新逻辑回归方程被进入仅仅有不稳定的工程的区域;地质的条件在大规模工程活动期间对山崩敏感。考虑这二逻辑回归结果产出一张新山崩危险性地图。两倍逻辑回归分析改进了非山崩预言精确性。在为逻辑回归的参数的计算期间,山崩密度被用来转变名字的变量到数字变量;这避免哑巴变量的一个过分地高的数字的创造。
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简介:我们评估了在北伊朗在里海附近在Tavalesh区域影响大米鱼耕作的采纳的因素。我们与无限制的问题进行了调查。数据随机从184个回答者(61个采用者和123非采用者)被收集从选择村庄取样了并且分析了使用逻辑回归和多反应分析。家庭尺寸,与一个扩展代理人的接触的数字,在扩展教育活动的参予,在社会机构的会员和农场工人的存在是为大米鱼耕作系统的采纳的最重要的社会经济的因素。另外,经济问题是采用者报导的最普通的问题。象存取的缺乏那样的另外的问题捞食物拨出,鱼的损失,高质量的鱼鱼种和脱水和差的水质量的存取的缺乏对很多个农民也重要。
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简介:Inthesystemofm(m≥2)seeminglyunrelatedregressions,weshowthattheGauss-Markovestimator(GME)ofanyregressioncoefficientshasuniquesimplifiedform,whichexactlyequalstotheonestepcovariance-adjustedestimatoroftheregressioncoefficients,andhenceweconcludethatforanyfinitek≥2thek-stepcovariance-adjustedestimatordegeneratestotheone-stepcovariance-adjustedestimatorandthecorrespondingtwo-stageAitkenestimatorhasexactlyonesimplifiedform.Also,theuniquesimplifiedexpressionoftheGMEisjusttheestimatorpresentedintheTheorem1ofWang’work[1988].Anewestimateofregressioncoefficientsinseeminglyunrelatedregressionsystem,ScienceinChina,SeriesA10,1033-1040].
简介:TheconcernoveroutliersisoldsinceBernoulli(see[12]),reviewedhistoricallyby[11]andupdatedwith[10]intheirencyclopediatextbook.Jamesetal.[46]usedsimulationtechniquetocomparesomerecentpublishedoutlierdetectionprocedures.Thehistoryofadeptanddiagnosisofoutliersistracedfromoldandpresencecomments.Theil-typeorRank,Brown-Mood,Lp,M,adaptiveM,GM,andTrimmed-Winsorizationestimatorsarethemostpopularestimatorsthatwewillreviewinthispaperasanapplicationtooutlieraccommodation.Wewillreviewandcomparethemostnumericalandgraphicaldisplaysbasedonresidualstoflagoutliers.
简介:M7.0Lushan地震触发了的s山崩的一个巨大的数字。印射的山崩危险性是很重要的。证据(悲痛)和逻辑回归(LR)的重量方法广泛地为LSM(印射的山崩危险性)被使用了。然而,限制仍然存在。悲痛能够估计每个因素的不同的班的影响,但是忽视在因素之间的关联。当它不能够评估不同的班的影响时,LR能在因素之中分析关系。这份报纸为LSM建议LR和悲痛的一个联合方法,利用他们的单个优点并且克服他们的限制。1289山崩的库存被使用:70%为为确认训练并且留下是选择随机的。11个山崩条件因素在模型被采用,结果用操作特征(巨鸟)曲线的接收装置被验证。结果证明LR悲痛模型比LR模型有更好的精确性,生产在有0.802成功的价值的曲线下面的一个区域并且0.791预兆,比LR模型的高(0.715成功并且0.722预兆)。悲痛和LR的联合方法能为印射的导致地震的山崩危险性提供精确性的有希望的水平,这因此被结束。
简介:RecentlyR.S.SinghhasstudiedtheempiricalBayes(EB)estimationinamultiplelinearregressionmodel.InthispaperweconsidertheEBtestofregressioncoefficientβforthismodel.WeworkouttheEBtestdecisionrulebyusingkernelestimationofmultivariatedensityfunctionanditsfirstorderpartialderivatives.Weobtainitsasymptoticallyoptimal(a.o.)propertyundertheconditionE||β||1<∞.ItisshownthattbeconvergenceratesofthisEBtestdecisionruleareO(n-(r-1)λ/p+r)undertheconditionE||β||pr/2-λ<∞.whereanintegerr>l,0
简介:APoissonregressionmodelandanegativebinomialregressionmodel(NBmodel)areoftenusedinareassuchasmedicineandeconomy,butrarelyinthedomesticforestrysector,especiallyintheforestfireforecasting.BasedonthedataofforestfireoccurrencesinDaxing’anlingregionin1980-2005,thispaperprofoundlyanalyzestheapplicationconditionsandtestmethodsofthetwomodels.TheAICmethodwasusedtocheckthefittinglevelofthemodelsandthecapabilityofthemodelsforforecastingforestfireswasdiscussed.ThisstudyprovidednecessarytheoreticalbasisanddatasupportfortheapplicationofthetwomodelsinthefieldofforestryinChina.
简介:Fittinglogarithmicbln(clx),a+bln(c+x)orreciprocalb/(c+x),a+b/(c+x)regressionmodelstodatabytheleastsquaresmethodasksforthedeterminationoftheclosureofthesetofeachtypeofthesefunctionsdefinedonafinitedomain.Itfollowsthataminimalsolutionmaynotexist.Butitdoesexistwhentheclosureisconsidered.
简介:Twodiagnosticsarepresentedforthetransformationofexplanatoryvariablesinregression.OneisbasedonthelikelihooddisplacementproposedbyCookandWeisberg(1982)forassessingtheinfluenceofindividualcasesonthemaximumlikelihoodestimateofatransformationparameter.Theotherisbasedonthelocalin-fluencetheoryproposedbyCook(1986)forassessingtheinfluenceofsmallperturba-tionsontheparameterestimates.Computationsarcperformedforadatasettoillus-tratetheusefulnessofthesediagnostics.
简介:Researchonjumpregressionfunc(?)onshasnotbeenadequateyetAccordingtotheinformationaboutthenumberofjumps,theirpositionsandjumpmagnitudes,jumpregressionfunctionscanbeclassifiedintoeighttypes.Thispaperdealsespeciallywiththesecondjumpregressionfunction.Firstofall,aconceptoftrimmedsplineestimateisproposedandwithitanL~2-consistentestimateofthesmoothingpartofthejumpregressionfunctionisobtained.ThisalongwiththeL~2-consistentestimateofjumpmagnitudeconstitutesanestimateofthesecondjumpregressionfunction.Thispaperdiscussesalsothecasethatthejumppositionshavesomeindeterminacy.Anewcriterionissuggestedanditsuniquesolutionderived.Intheend,afewnumericalresultsaregiven.
简介:AbstractIt has been reported that liver fibrosis could be reversed after eliminating liver injuries. This article systematically summarizes the evidence of fibrosis regression based on histology, liver stiffness, and serum biomarkers, and discusses several clinically relevant challenges. Evidence from liver biopsy has been regarded as the gold standard in the assessment of fibrosis regression. Semi-quantitative staging and grading systems are traditionally and routinely used to define regression. Recently, the predominantly regressive, indeterminate, and predominantly progressive score was proposed, based on the regressive features from "hepatic repair complex" , to provide additional information regarding the quality of fibrosis. For non-invasive assessment, although liver stiffness and serum biomarkers could be applied to reflect the dynamic changes of liver fibrosis, other confounding factors such as liver inflammation have to be considered. In conclusion, both histology and non-invasive methods can provide evidence regarding fibrosis regression. The predictive value of fibrosis regression in long-term prognosis warrants further investigation.