关于假设检验中的双侧检验与单侧检验

本文首先介绍了小概率原理和假设检验的基本概念,其次又给出了关于总体平均数及总体频率的假设检验方法,可详细地分为双侧检验与单侧检验。最后,又列举了一些如何利用假设检验的实例,这些例子都具有一定的参考价值与使用价值。     

林业数理统计方法讲座(四) 假设检验

一、假设检验的基本概念统计推断中除参数估计外,另一类大问题就是假设检验。所谓假设检验是先对所研究的总体作去某种假设,这种假设是一种对总体分布参数或分布类型的一种叙述,然后通过样本和适当的统计量,检验这个假设是否成立。假设检验又称差异显著性检验。假设检验中作为对所作假设是否接受判断标准要用到“小概率原理”,即“概率很小的事件在一次试验中是几乎不至于发生的”原理。这是一条人们从实践中总结出来的概率原理。检验的一般步骤为:在对总体某种假设下(通常称为原假设,记为 Ho),根据     

不平衡巢式设计遗传模型分析

虽然巢式试验设计在动植物育种中得到广泛应用,但是在不平衡数据条件下有关遗传参数估计和假设检验统计量的计算还存在着很多问题。文中针对不平衡数据条件下的巢式试验设计,使用固定效应模型和随机效应模型估计相关的遗传参数并进行相应的统计假设检验。对于固定效应模型,使用约束线性模型方法推导出亲本配合力估计及亲本间配合力假设检验统计量的计算公式。对于随机效应模型,采用混合线性模型中的方差分析法,推导出方差分量估计的计算公式,并给出方差分量估计标准误以及方差分量假设检验统计量的计算方法,进而给出遗传力计算公式及其标准误的近似计算方法。最后,用VC++编写多种形式巢式设计遗传模型的各种遗传参数估计和假设检验统计量计算的Windows应用软件,供林木遗传育种工作者使用。     

龙岩市鸟兽类与其栖息地生境的关系

通过对鸟兽类野生动物在不同生境类型的分布密度进行比较和假设检验,分析了不同物种对其栖息地生境的需求.     

正态分布假设检验程序

正态分布在各种统计分析中,在森林经营中经常用到,较为方便快捷.现基于CASIOfx-4500P机型研究正态分布的假设检验程序。     

BS111型拌胶机施胶均匀度的检测分析

依据检测数据,采用数理统计学中假设检验的方法对BS111型拌胶机施胶均匀度进行判断,从而得出该机施胶均匀度性能满足设计要求的结论。     

会同杉木人工林的树高分布模型

利用湖南会同县１７０块杉木人工林样地资料，用Ｗｅｉｂｕｌ分布函数模拟出直径分布规律．并以此为基础，结合树高曲线理论模型，推导出树高分布预估模型，同时进行了精度分析和假设检验     

林业有害生物防治试验中的回归分析问题

在林业有害生物防治试验中,回归分析是一种常用的数理统计方法,可靠性检验是对回归关系的重要评估措施。利用Excel的强大制图功能,可便捷地获得回归曲线,利用R值进行F-检验,对回归曲线进行假设检验的可靠性分析。     

小概率原理在林火预报中的应用

对于林火预报工作中一些不能准确预测未来或尚未发生的事件,我们可以对火灾历史资料进行统计分析,找出林火发生发展规律,应用小概率事件原理,对林火发生的可能性进行预估假设检验,从而解决问题。本文将通过实例应用来说明。     

文科类《统计学》教学实践探索——以总体均值区间估计为例

参数区间估计是统计学教学的重点和难点,也是后续假设检验学习的基础。考察许多教材发现:参数区间估计章节处理过于简单,致使按照教材讲解学生难以理解。教学实践过程中,从抽样分布理论出发,图文并茂,分四步讲解参数的区间估计,产生了良好的教学效果。     

光箨篌竹单竹产量模型的初步研究

应用贵州铜仁市郊0.67万hm~2光箨篌竹的310株标准竹为材料,分别用眉径(D_(om))、竹高(h_0)、枝下高(h_1)3个指标对经济产量(W_1)和生物产量(W_2)进行数学模型拟合,经过相关系数R和标准差S的比较分析,采用F检验和线性回归相关系数的假设检验,并作模型的实际验证,选出8个较优模型,同时得出径级产量表,这将对光箨篌竹的产量预测有重要参考价值。     

Open woodland in Europe in the Mesolithic and in the Middle Ages: Can there be a connection?

In Grazing Ecology and Forest History F.W.M. Vera published his hypothesis that Europe's primeval vegetation was not closed forest but a more open, park-like landscape maintained by the grazing of large herbivores. The palaeoecological evidence has been re-examined a number of times, however, Vera's research and conclusions about more recent periods (ca. 500–1900 a.d.) have so far been neglected. These, nonetheless, are equally significant elements in the testing of the hypothesis, and deserve to be evaluated. It is argued in this paper that historical sources could be used in testing the hypothesis; however, analysis should concentrate on particular areas and periods and derive a synthesis from these. Vera mixes sources from many regions and periods in the same analysis, which therefore does not provide useful information about the hypothesis. Furthermore, Vera's analysis is based on the assumption that early medieval written sources depict a landscape that is in direct connection with the pre-Neolithic open vegetation, although in some early medieval landscapes domestic animals replaced the original large herbivores. He also claims that medieval coppices were formed straight out of this primeval vegetation. However, current landscape archaeological research shows that areas unaffected by human activity were virtually non-existent in the European lowlands by the Early Middle Ages, therefore early medieval Royal Forests and high medieval coppices were not formed out of primeval ‘wilderness.’ Because there is no direct connection between pre-Neolithic and medieval landscapes – although they can be analogous – the historical ecological evidence in Grazing Ecology and Forest History is irrelevant to the hypothesis. The hypothesis could only be tested if it were first proved that at a particular place the pre-Neolithic vegetation survived until the Early Middle Ages.     

Modelling diameter class distribution with a second-order matrix model

Matrix models of forest dynamics rely on four hypotheses: independence hypothesis, Markov’s hypothesis, Usher’s hypothesis, and temporal homogeneity hypothesis. We investigate the consequences of relaxing Markov’s hypothesis, allowing the state of the tree at time t to depend on its states at time t−1 and t−2. The methodology for building and testing the relevance of second-order matrix model is thus proposed. The derivation of second-order transition probabilities turns to be sensitive to the width of the diameter classes. A strategy for choosing diameter classes is proposed. A second-order matrix model is then built for a tropical rain-forest in French Guiana. A different behaviour is detected between small (dbh ≤30 cm) and large trees, the smaller trees being more sensitive to their past history: small trees that have well grown have a tendency to grow well again, and small trees that have not grown tend to have a higher probability to die. The widths of the diameter classes that are selected are much less than the widths usually retained, that favour first-order selection.     

A hypothesis about the interaction of tree dominance and stand production through stand development

The development of forests over time involves changes in rates of growth of trees and stands, and changes in the competition and dominance between trees plays a large role in the overall development of stands. A hypothesis proposes that changes in the growth of trees and stands result from regular changes in dominance and the efficiency of resource use by dominant and non-dominant trees. Dominance is low prior to canopy closure, and efficiency of resource use is high for all trees. Increasing dominance near canopy closure reduces the efficiency of resource use by non-dominant trees, lowering overall stand growth. Later in stand development, the efficiency of resource use also declines for the largest trees, reducing the level of dominance in the stand. The dominance part of this hypothesis was examined for 150 years of stand development in two mixed-species stands in the Coast Range of Oregon. A quantitative index of dominance was minimal prior to the peak in stand growth near age 25–30 years, and then increased sharply as stand productivity declined. Dominance then declined after age 100 years as the growth rate of the 300 largest trees/ha began to decline. The dominance portion of the hypothesis was supported, and further testing may be useful.     

杉木种源对断面积模型影响的检验和比较

对鸡公山、大岗山和洪雅种源试验的调查材料,用随机效应检查和固定效应检查两种方法检验和比较了同一地区不同种源对断面积生长模型的影响。结果表明,种源试验中采用随机效应检查较好,固定效应检查容易造成差异显著的误判。随机效应检查的结果表明,同一地区不同种源的断面积模型相同。     

小陇山林区日本落叶松人工林培育目标探讨

以小陇山林区日本落叶松人工林156块样地调查数据,应用理查德曲线进行林分平均树高和胸径生长模型的拟和,通过回归假设F检验,拟和的生长模型,在F0.05水平与实际值差异不显著;利用拟和的导向曲线方程,以树高为基础,将小陇山林区日本落叶松林分立地划分为5个地位级。同时以小陇山沙坝实验基地引种试验林为例,分析了林分生长、单木生长过程和趋势。     

Problems of hypothesis testing of regressions with multiple measurements from individual sampling units

Problems with hypothesis testing arise when regression analysis is applied to data sets which contain multiple measurements from individual sampling units. These sampling units might be individual trees from each of which several measurements were taken at different positions on each tree, or they might be individual plots in each of which many trees were measured, or they might be individual plots each of which was measured at several ages. The problems arise because application of ordinary least-squares regression to such data sets leads to underestimates of the covariance matrix of the parameter estimates and the residual variance of the regression equation. Thus, it would not be possible to carry out properly the statistical tests involved in matters such as a covariance analysis or the determination of the most appropriate form of the equation to be fitted to a data set. Theory already exists to solve these problems in cases where the measurements are all made at the same set of conditions in each sampling unit: this is often the case with data from designed experiments. Forestry data sets are often not of this nature and these solutions are generally inappropriate.Using a simple example, the present work explains how problems of hypothesis testing of regressions arise with these data sets. Six theoretical attempts to solve the problems are reviewed. All these theories apply only asymptotically, that is when the number of sampling units is very large. Their small sample behaviour is unknown and their usefulness is therefore questioned. Practical methods for handling such data sets are suggested. In particular, a technique to analyze data in two stages has been found most useful. A number of examples of forestry problems from the literature are described to demonstrate the range of circumstances under which these difficulties occur.     

Summer drought: a driver for crown condition and mortality of Norway spruce in Norway

Summer drought, i.e. unusually dry and warm weather, has been a significant stress factor for Norway spruce in southeast Norway during the 14 years of forest monitoring. Dry and warm summers were followed by increases in defoliation, discolouration of foliage, cone formation and mortality. The causal mechanisms are discussed. Most likely, the defoliation resulted from increased needle‐fall in the autumn after dry summers. During the monitoring period 1988–2001, southeast Norway was repeatedly affected by summer drought, in particular, in the early 1990s. The dataset comprised 455 ‘Forest officers’ plots’ with annual data on crown condition and mortality. Linear mixed models were used for estimation and hypothesis testing, including a variance–covariance structure for the handling of random effects and temporal autocorrelation.