A survey of robust statistics

We argue that robust statistics has multiple goals, which are not always aligned. Robust thinking grew out of data analysis and the realisation that empirical evidence is at times supported merely by one or a few observations. The paper examines the outgrowth from this criticism of the statistical method over the last few decades. This research was supported in part by the Swiss National Science Foundation. An erratum to this article can be found at     

A brief survey of nonparametric statistics

The area of non-parametrie statistics has briefly been surveyed. The survey is limited to univariate fixed-sample size problems     

Some robust two-sample test statistics based on m-estimators of location

This paper describes a simulation experiment that compares the performance, in terms of the size and a function of the power, of four two-sample test statistics based on M-estimators for location. M-esti-mates are chosen to ensure similar levels of breakdown point, gross error sensitivity and as far as possible, similar rejection point. Two pairs of sample size and six different distributions are involved. Matching 97.5% critical values for the statistics are determined.     

Usefulness of robust estimators in sample survey

It Is illustrated that the adaptation of robust estimators, Tiku's (1967, 1978, 1980) modified maximum likelihood estimators for example, in sample survey can lead to considerable improvements In efficiencies in estimating the mean of a finite population (a random sample of Independent observations from a super-popularlon). In this paper, however, we confine our attention to symmetric super-populations     

A comparison of chi-squared statistics for testing homogeneity of survey data:High School and Beyond survey

The performance of several test statistics for comparing vectors of propor tions from certain survey data was compared. The statistics were used to analyze a subsample of data from the 'High School and Beyond' survey. These tests include the Wald test statistic X2w and the modified Wald test statistic FW, the chi-squared test statistic X2rSB and its modification FRSB, a test X2dmb based on a probability model, and a method of moments approach, X2H. Data were also simulated based on two-stage cluster sampling design and the type I error level, and the power of these tests was obtained for selected combinations of parameter values. The statistics X2DMB XRSB, FRSB and X2H performed well both for a small number of clusters or a small number of units within clusters. The power performance of these tests is quite stable. Approximate intervals were constructed for design effect constants. Methods of estimating these constants based on a normality assumption worked best.     

Studentized robust statistics for,main effects in a two-factor manova

Multiresponse experiments in two-faoior manova are considered. StalibLical procedures of the test and estimation, based on studentized robust statistics. for location parameters in the models arc piupused. Large sample properties of their procedures as the cell sizes tend to infinity are investigated. Although Fisher's consistency is assumed in the theory ol ili-estimators, it is not needed. in this paper. For the univariate case, it is found that the asymptotic relative efficiencies (ARE's) of the proposed procedures relative to classical procedures agrees with the classical A/Sisresults of Huber's one sample Mestimator relative to the sample mean. By simulation studies, it can be seen that the proposed estimators are more efficient than the least squares estimators except for the case where the underlying distribution is normal     

Robustness of MML estimators based on censored samples and robust test statistics

We investigate the efficiences of Tiku's (1967) modified maximum likelihood estimators μ_c and σ_c (based on symmetrically censored normal samples) for estimating the location and scale parameters μ and σ of symmetric non-normal distributions. We show that μ_c and σ_c are jointly more efficient than x? and s for long-tailed distributions (kurtosis $\text{β}{}_2{}^1\text{=}\text{μ}{}_4\text{μ}{}_2{}^2\text{>4.2, β}{}_2{}^1\text{= 4.2}$ for the Logistic), and always more efficient than the trimmed mean μT and the matching sample estimate σ_T of σ. We also show that μ_c and σ_c are jointly at least as efficient as some of the more prominent “robust” estimators (Gross, 1976). We show that the statistic $\text{t}{}_{\mathrm{c}}\text{= μ}{}_{\mathrm{c}}\text{m}\text{σ}{}_{\mathrm{c}}\text{, m = n ?2r + 2rβ}$ (r is the number of observations censored on each side of the sample and β is a constant), is robust and powerful for testing an assumed value of μ. We define a statistic T_c (based on μ_c andσ_c) for testing that two symmetric distributions are identical and show that T_c is robust and generally more poweerful than the well-known nonparametric statistics (Wilcoxon, normal-score, Kolmogorov-Smirnov), against the important location-shift alternatives. We generalize the statistic T_c to test that k symmetric distibutions are identical. The asymptotic distributions of t_c and T_c are normal, under some very general regularity conditions. For small samples, the upper (lower) percentage points of t_c and T_c are shown to be closely approximated by Student's t-distributions. Besides, the statistics μ_c and σ_c (and hence t_c and T_c) are explicit and simple functions of sample observations and are easy to compute.     

Designing cancer immunotherapy trials with delayed treatment effect using maximin efficiency robust statistics

The indirect mechanism of action of immunotherapy causes a delayed treatment effect, producing delayed separation of survival curves between the treatment groups, and violates the proportional hazards assumption. Therefore using the log‐rank test in immunotherapy trial design could result in a severe loss efficiency. Although few statistical methods are available for immunotherapy trial design that incorporates a delayed treatment effect, recently, Ye and Yu proposed the use of a maximin efficiency robust test (MERT) for the trial design. The MERT is a weighted log‐rank test that puts less weight on early events and full weight after the delayed period. However, the weight function of the MERT involves an unknown function that has to be estimated from historical data. Here, for simplicity, we propose the use of an approximated maximin test, the V₀ test, which is the sum of the log‐rank test for the full data set and the log‐rank test for the data beyond the lag time point. The V₀ test fully uses the trial data and is more efficient than the log‐rank test when lag exits with relatively little efficiency loss when no lag exists. The sample size formula for the V₀ test is derived. Simulations are conducted to compare the performance of the V₀ test to the existing tests. A real trial is used to illustrate cancer immunotherapy trial design with delayed treatment effect.     

A robust biplot

This paper introduces a robust biplot which is related to multivariate M-estimates. The n × p data matrix is first considered as a sample of size n from some p-variate population, and robust M-estimates of the population location vector and scatter matrix are calculated. In the construction of the biplot, each row of the data matrix is assigned a weight determined in the preliminary robust estimation. In a robust biplot, one can plot the variables in order to represent characteristics of the robust variance-covariance matrix: the length of the vector representing a variable is proportional to its robust standard deviation, while the cosine of the angle between two variables is approximately equal to their robust correlation. The proposed biplot also permits a meaningful representation of the variables in a robust principal-component analysis. The discrepancies between least-squares and robust biplots are illustrated in an example.     

Energy statistics: A class of statistics based on distances

Energy distance is a statistical distance between the distributions of random vectors, which characterizes equality of distributions. The name energy derives from Newton's gravitational potential energy, and there is an elegant relation to the notion of potential energy between statistical observations. Energy statistics are functions of distances between statistical observations in metric spaces. Thus even if the observations are complex objects, like functions, one can use their real valued nonnegative distances for inference. Theory and application of energy statistics are discussed and illustrated. Finally, we explore the notion of potential and kinetic energy of goodness-of-fit.     

A nonsymbolic statistics course

A new statistics course Is being taught at the University of Kentucky which does not require students to learn the symbolic language uf statistics (the formulas) Students who will never take a traditional "methods"course in satistics learn to become better consumer of the satistics fed them daily by different news media.other students who realised that munch satistics await them in graduate see this course as a good startingpoint     

A novel in statistics

Jane Yardley spends her days organising clinical trials. By night she writes successful novels. Her latest involves mystery, wartime crime and Sibelius; and its heroine is a biostatistician. Why? Chocolate teddybears, a father who worked with toxic chemicals and a bookmaker's clerk made her do it …     

Doubly robust point and variance estimation in the presence of imputed survey data

Imputation is often used in surveys to treat item nonresponse. It is well known that treating the imputed values as observed values may lead to substantial underestimation of the variance of the point estimators. To overcome the problem, a number of variance estimation methods have been proposed in the literature, including resampling methods such as the jackknife and the bootstrap. In this paper, we consider the problem of doubly robust inference in the presence of imputed survey data. In the doubly robust literature, point estimation has been the main focus. In this paper, using the reverse framework for variance estimation, we derive doubly robust linearization variance estimators in the case of deterministic and random regression imputation within imputation classes. Also, we study the properties of several jackknife variance estimators under both negligible and nonnegligible sampling fractions. A limited simulation study investigates the performance of various variance estimators in terms of relative bias and relative stability. Finally, the asymptotic normality of imputed estimators is established for stratified multistage designs under both deterministic and random regression imputation. The Canadian Journal of Statistics 40: 259–281; 2012 © 2012 Statistical Society of Canada     

物流统计初探

一、物流统计调查的必要性物流包括运输、仓储、包装、装卸搬运、流通加工、配送、信息等职能 ,社会经济运行中生产、流通、消费等环节均涉及到物流。随着经济全球化、一体化的发展和现代科学技术、管理技术在物流行业的应用 ,使原来分散于不同经济领域和环节的相对独立的物流功能发生了密切的联系 ,统一为综合物流系统 ,这不仅提高了物流本身的运作效率 ,而且更好地适应了市场上用户对物流的要求 ,使物流业发展成为有别与传统运输、仓储行业的新兴产业。现代物流业一般由交通运输、储运、货代、流通加工和配送等行业构成。交通运输行业包括…     

A robust principal component analysis

This work is concerned with robustness in Principal Component Analysis (PCA). The approach, which we adopt here, is to replace the criterion of least squares by another criterion based on a convex and sufficiently differentiable loss function ρ. Using this criterion we propose a robust estimate of the location vector and introduce an orthogonality with respect to (w.r.t.) ρ in order to define the different steps of a PCA. The influence functions of a vector mean and principal vectors are developed in order to provide method for obtaining a robust PCA. The practical procedure is based on an alternative-steps algorithm.     

A robust process capability index

The existing process capability indices (PCI's) assume that the distribution of the process being investigated is normal. For non-normal distributions, PCI's become unreliable in that PCI's may indicate the process is capable when in fact it is not. In this paper, we propose a new index which can be applied to any distribution. The proposed indexC_f:, is directly related to the probability of non-conformance of the process. For a given random sample, the estimation of C_f boils down to estimating non-parametrically the tail probabilities of an unknown distribution. The approach discussed in this paper is based on the works by Pickands (1975) and Smith (1987). We also discuss the construction of bootstrap confidence intervals of C_f: based on the so-called accelerated bias correction method (BC _a:). Several simulations are carried out to demonstrate the flexibility and applicability of C_f:. Two real life data sets are analyzed using the proposed index.     

A robust QTL mapping procedure

In quantitative trait linkage studies using experimental crosses, the conventional normal location-shift model or other parameterizations may be unnecessarily restrictive. We generalize the mapping problem to a genuine nonparametric setup and provide a robust estimation procedure for the situation where the underlying phenotype distributions are completely unspecified. Classical Wilcoxon–Mann–Whitney statistics are employed for point and interval estimation of QTL positions and effects.