Testing For Uniformity Research Articles

Development of a methodology for assessing economically useful signs of hyssop

Hyssop (Hyssopus officinalis L.) refers to valuable spicy-aromatic, essential oil and medicinal crops and is widely used in traditional and folk medicine, perfumery, cosmetology, cooking and food industry. The main directions of selection of hyssop are increasing productivity, obtaining forms adapted to industrial cultivation technology, resistance to pests and diseases, valuable chemical and biochemical composition, different terms of onset of economic suitability, honey productivity, zoning (suitability for cultivation in specific soil and climatic conditions). The article presents the results of studies on the evaluation of the breeding material of hyssop by a complex of economically useful morphological, morphometric and phenological traits, including a new zoned author’s variety of the Belarusian State Agricultural Academy Zaveya. As a result of the research, the methodology for testing the distinctiveness, uniformity and stability of hyssop has been improved, which makes it possible to optimize the breeding process of this crop and conduct an extended assessment of the identification of varieties during state variety testing. The national methodology for testing for distinctiveness, uniformity and stability provides an opportunity for breeders to pay attention to the relevant characteristic and distinctive features of hyssop, which will contribute to the effective conduct of further breeding work to create forms and varieties with various economically valuable properties.

Testing uniformity on the circle using spacings when data are rounded

Testing for uniformity for any given data set on the circle is an important first step before any further inference. One important class of tests are those based on spacings, which assume that the data are measured on a continuous scale. In practice however, the observed data may come grouped, or the recorded observations may be rounded values. Ignoring this fact can result in incorrect Type I error probabilities and inference, especially if the degree of rounding is severe or if the sample size is large. In this article, we propose a simple modification to such rounded data, which then allows us to continue to use the Rao’s spacing test and its exact critical values, without affecting the probability of Type I error. We provide theoretical justification for the suggested modification, as well as simulation studies that demonstrate its strong and robust performance.

Work Analysis of Wire Handling Process Using Work Sampling Method and Standard Time Determination

Productivity is one of the main factors in the company where productivity will affect the production output. This research was conducted on the wire handling process and the method used was work sampling and standard time determination, where previously statistical calculations were carried out to see the uniformity of the data and also the adequacy of the data. The method used in this study is the work sampling method, where time data sampling is done using a table of random numbers. In addition, standard time calculations are also carried out. The results obtained are productive activities as many as 160 out of 200 observations or by 80% and non-productive activities by 40 out of 200 observations or by 20%. Statistical testing for data uniformity shows that the observation data from the first day to the fifth day are (1) 0.80 (2) 0.80 (3) 0.825 (4) 0.80 (5) 0.775 still within the upper control limit and the lower control limit, which are 1.1 respectively. and 0.5. Sampling of the work that has been done can be concluded that with a 95% confidence level the percentage of working time that can be used productively by workers is 80% with a conclusion error rate of 10%. The standard time calculation obtained is 125.12 minutes for the wire handling process where this can still be improved if the operator is given training.

Work Analysis of Wire Handling Process Using Work Sampling Method and Standard Time Determination at PT. YMH

Productivity is one of the main factors in the company where productivity will affect the production output. This research was conducted on the wire handling process and the method used was work sampling and standard time determination, where previously statistical calculations were carried out to see the uniformity of the data and also the adequacy of the data. The method used in this study is the work sampling method, where time data sampling is done using a table of random numbers. In addition, standard time calculations are also carried out. The results obtained are productive activities as many as 160 out of 200 observations or by 80% and non-productive activities by 40 out of 200 observations or by 20%. Statistical testing for data uniformity shows that the observation data from the first day to the fifth day are (1) 0.80 (2) 0.80 (3) 0.825 (4) 0.80 (5) 0.775 still within the upper control limit and the lower control limit, which are 1.1 respectively. and 0.5. Sampling of the work that has been done can be concluded that with a 95% confidence level the percentage of working time that can be used productively by workers is 80% with a conclusion error rate of 10%. The standard time calculation obtained is 125.12 minutes for the wire handling process where this can still be improved if the operator is given training.

Graphical test for discrete uniformity and its applications in goodness-of-fit evaluation and multiple sample comparison

Assessing goodness of fit to a given distribution plays an important role in computational statistics. The probability integral transformation (PIT) can be used to convert the question of whether a given sample originates from a reference distribution into a problem of testing for uniformity. We present new simulation- and optimization-based methods to obtain simultaneous confidence bands for the whole empirical cumulative distribution function (ECDF) of the PIT values under the assumption of uniformity. Simultaneous confidence bands correspond to such confidence intervals at each point that jointly satisfy a desired coverage. These methods can also be applied in cases where the reference distribution is represented only by a finite sample, which is useful, for example, for simulation-based calibration. The confidence bands provide an intuitive ECDF-based graphical test for uniformity, which also provides useful information on the quality of the discrepancy. We further extend the simulation and optimization methods to determine simultaneous confidence bands for testing whether multiple samples come from the same underlying distribution. This multiple sample comparison test is useful, for example, as a complementary diagnostic in multi-chain Markov chain Monte Carlo (MCMC) convergence diagnostics, where most currently used convergence diagnostics provide a single diagnostic value, but do not usually offer insight into the nature of the deviation. We provide numerical experiments to assess the properties of the tests using both simulated and real-world data and give recommendations on their practical application in computational statistics workflows.

K. V. KLEMESHOVA, T. YU. GABUEVA PECULIARITIES OF FORMATION OF LARGE-FLOWERED CHRYSANTHEMES FOR OBTAINING CUT IN A WET SUBTROPICAL CLIMATE

Chrysanthemum is one of the leading crops of commercial floriculture. Within garden groups and classes, chrysanthemums are divided according to cultivation methods, shape and size of the inflorescences. For varieties grown on a cut, a group of large-flowered (with a diameter of inflorescences of 12-25 cm), small-flowered (4-10 cm) chrysanthemums and santini (from 2 to 4 cm) is distinguished. Having a limited assortment of chrysanthemum garden, in a humid subtropical climate, it is possible to form a largeflowered (single-headed, disbud) and small-flowered (spray) cut. The purpose of the research was to study the peculiarities of formation of large-flowered chrysanthemums (Chrysanthemum×hortorum Bailey) to obtain cut in the humid subtropics of Russia. The objects of research were large-flowered and small-flowered varieties of chrysanthemums of foreign and domestic breeding. The studies were carried out in the open ground of the Department of Agricultural Engineering and Nursery of the Federal Research Center the Subtropical Scientific Center of the Russian Academy of Sciences. Scientific research was carried out according to the methodology of State variety testing of agricultural crops and the methodology of testing for distinctness, uniformity and stability of chrysanthemum (perennial) Chrysanthemum spec. ‘Sevan’, ‘Baltica White’, ‘Granada’ and ‘Zembla Brasil’ are large-flowered varieties, which have bush peduncles of good commercial quality with large inflorescences of saturated shades. In turn, from small-flowered garden forms ‘Zembla White’, ‘Annecy White’ and ‘Westland Regal’ with regular pinching, you can grow a large-flowered cut of chrysanthemums. It was revealed the relationship between biometric characteristics in order to determine additional diagnostic features of the possibility of the formation of large-flowered inflorescences. So, the diameter of the inflorescence is the most significant parameter for research which has significant positive relationships with the diameter of the peduncle and the length of the extreme ray flower. It will allow determining the possibility of growing the variety in one form or another, depending on the needs of production, at the initial stages of introduction and variety study.

Optimising compression testing for strain uniformity to facilitate microstructural assessment during recrystallisation

Predicting the kinetics of recrystallisation in metals, and recrystallised grain size distributions, is one the key approaches to controlling and refining grain size during metal processing, which typically increases strength and toughness/ductility. Recrystallisation prediction models and equations are supported by lab-based simulations that can systematically assess recrystallisation over a range of temperatures and strains for different materials and starting grain sizes. This work uses modelling and experimental verification to assess the different commonly used compression test sample geometries to determine strain uniformity and potential sources of error in microstructural assessment and proposes a modified geometry that increases the area of constant known strain. Whilst flow stress measurements in all samples showed good agreement. It has been shown that the new plane strain geometry offers a more consistent, homogeneous strain through the sample such that the large number of grains needed for accurate grain size distribution measurement can be readily achieved. Over double the area of ±10% of the target strain was achieved in the modified plane strain sample compared to a conventional uniaxial specimen, this area was also shown to be more conducive to metallographic assessment and offers in excess of 1500 grains of 250 μm to be assess per cross-sectional slice.

On the asymptotic properties of a certain class of goodness-of-fit tests associated with multinomial distributions

The object of study is the problem of testing for uniformity of the multinomial distribution. We consider tests based on symmetric statistics, defined as the sum of some function of cell-frequencies. Mainly, attention is focused on the class of power divergence statistics, in particular, on the chi-square and log-likelihood ratio statistics. The main issue of the article is to study the asymptotic properties of tests at the concept of an intermediate setting, when the asymptotic power of tests are bounded away from zero and one, while sequences of alternatives converge to the hypothesis, but not too fast.

An Empirical Likelihood Ratio-Based Omnibus Test for Normality with an Adjustment for Symmetric Alternatives

An omnibus test for normality with an adjustment for symmetric alternatives is developed using the empirical likelihood ratio technique. We first transform the raw data via a jackknife transformation technique by deleting one observation at a time. The probability integral transformation was then applied on the transformed data, and under the null hypothesis, the transformed data have a limiting uniform distribution, reducing testing for normality to testing for uniformity. Employing the empirical likelihood technique, we show that the test statistic has a chi-square limiting distribution. We also demonstrated that, under the established symmetric settings, the CUSUM-type and Shiryaev–Roberts test statistics gave comparable properties and power. The proposed test has good control of type I error. Monte Carlo simulations revealed that the proposed test outperformed studied classical existing tests under symmetric short-tailed alternatives. Findings from a real data study further revealed the robustness and applicability of the proposed test in practice.

On the consistency of the spacings test for multivariate uniformity, including on manifolds

Abstract We give a simple conceptual proof of the consistency of a test for multivariate uniformity in a bounded set K ⊂ ℝd that is based on the maximal spacing generated by independent and identically distributed points X1, . . ., Xn in K, i.e. the volume of the largest convex set of a given shape that is contained in K and avoids each of these points. Since asymptotic results for the d > 1 case are only availabe under uniformity, a key element of the proof is a suitable coupling. The proof is general enough to cover the case of testing for uniformity on compact Riemannian manifolds with spacings defined by geodesic balls.

Bayesian goodness of fit tests: a conversation for David Mumford

The problem of making practical, useful goodness of fit tests in the Bayesian paradigm is largely open. We introduce a class of special cases (testing for uniformity: have the cards been shuffled enough; does my random generator work) and a class of sensible Bayes tests inspired by Mumford, Wu and Zhu. Calculating these tests presents the challenge of 'doubly intractable distributions'. In present circumstances, modern MCMC techniques are up to the challenge. But many other problems remain. Our paper is didactic, we hope to induce the reader to help take it further.

DUS characterization of rice hybrids and their parental lines using morphological marker

A plant variety is a genetically related plant group obtained by breeder, as a result of long and thoughtful process. A new cultivator is an important means of enhancing production and productivity of cultivated plants. Their fruit quality and resistance to diseases, thus helping in increasing the excellence of agriculture. Characterization of plant varieties in context of intellectual property rights is stimulated by the recent agreements within the framework of the World Trade Organization (WTO). The requirements of these activities vary, e.g. the varietal registration process involving testing for Distinctness, Uniformity and Stability (DUS) requiresa description of a newly bred variety be produced and compared to all existing varieties in common knowledge. These characters suffer from the limitations of number, interaction with the environment in which the variety grows and subjectivity in decision-making. The genuineness of variety is one of the most important characteristics of quality seed. In addition, seed certification, which forms a link between variety registration and seed production, involve assessment, varietal identification and purity to assure the quality of seed marked to farmer or grower. Characterization of four hybrids such as NARENDRA SANKAR DHAN 2, Rajlaxmi, Ajay and CR Dhan 701 their parental lines such as IR58025A, NDR3026-3IR, CRMS32A, IR42266-29-3R, CRMS31A, CRL22R and IR42266-29-3R based on distinguishing characters could differentiate the hybrids and parental lines.

Testing for uniformity of ultra-high energy cosmic ray arrival directions

Arrival directions of ultra-high energy cosmic rays (UHECRs) exhibit mainly an isotropic distribution with some small deviations in particular energy bins. In this paper, the Yakutsk array data are tested for circular uniformity of arrival directions in right ascension (RA) using two methods appropriate for the energy ranges below and above [Formula: see text] eV. No statistically significant deviation from uniformity is found in the arrival directions of cosmic rays (CRs) detected within the observation period 1974–2000.

A data-driven smooth test of symmetry

In this paper we propose a data driven smooth test of symmetry. We first transform the raw data via the probability integral transformation according to a symmetrized empirical distribution, and show that under the null hypothesis of symmetry, the transformed data has a limiting uniform distribution, reducing testing for symmetry to testing for uniformity. Employing Neyman’s smooth test of uniformity, we show that only odd-ordered orthogonal moments of the transformed data are required in constructing the test statistic. We present a standardized smooth test that is distribution-free asymptotically and derive the asymptotic behavior of the test and establish its consistency. Extension to dependent data case is discussed. We investigate the finite sample performance of the proposed tests on both homogeneous and mixed distributions (with unobserved heterogeneity). An empirical application on testing symmetry of wage adjustment process, based on heterogeneous wage contracts with different durations, is provided.

Linear rank tests of uniformity: understanding inconsistent outcomes and the construction of new tests

Several nonparametric tests exist to test for differences among alternatives when using ranked data. Testing for differences among alternatives amounts to testing for uniformity over the set of possible permutations of the alternatives. Well-known tests of uniformity, such as the Friedman test or the Anderson test, are based on the impact of the usual limiting theorems (e.g. central limit theorem) and the results of different summary statistics (e.g. mean ranks, marginals, and pairwise ranks). Inconsistencies can occur among statistical tests’ outcomes – different statistical tests can yield different outcomes when applied to the same ranked data. In this paper, we describe a conceptual framework that naturally decomposes the underlying ranked data space. Using the framework, we explain why test results can differ and how their differences are related. In practice, one may choose a test based on the power or the structure of the ranked data. We discuss the implications of these choices and illustrate that for data meeting certain conditions, no existing test is effective in detecting nonuniformity. Finally, using a real data example, we illustrate how to construct new linear rank tests of uniformity.

Improvements of curing operations for Portland cement concrete pavement

Curing of concrete has substantial effects on the performance of Portland cement concrete (PCC) pavement. The effectiveness of membrane-forming curing compound depends on the quality of curing materials, time of curing compound application in relation to bleeding and evaporation, and amount and uniformity of curing materials applications. This study presents the efforts to develop simple compliance testing for application rate and uniformity. Compliance testing was based on the speed control of a curing machine utilizing a non-contact Doppler radar speed sensor and wireless data logger system. The findings from trial implementations of this method in PCC paving projects include: (1) speed control of a curing machine could be the most practical and simplest method for compliance testing; (2) Doppler sensor and wireless data logger showed fairly good performance and can be an effective and practical curing compliance testing system; and (3) as wind speed increases, the loss of curing compound tends to increase nearly proportionally.

Uniformity tests under quantile categorization

PurposeIn statistical inference, goodness of fit techniques are frequently used to decide if an observed sample X1=x1, … ,Xn=xn can be considered as independent realizations from a proposed cumulative distribution function F0(x). When goodness of fit tests are based on categorized data, they usually rely on relative frequencies of intervals or on sample quantiles. In this paper, comparisons between frequency‐based and quantile‐based power divergence test statistics are presented to test the hypothesis of uniformity in the interval (0,1) against different families of alternatives and some recommendations are given.Design/methodology/approachDivergence test statistics proposed by Cressie and Read are used and Monte Carlo simulation experiments are carried out. Both methods of categorization are applied separately to test the hypothesis of uniformity in the interval (0,1) and power comparisons are done for the families of alternatives proposed by Stephens. Next, a combined analysis is performed with the test statistics which have given the best results in each kind of categorization.FindingsResults obtained by using quantile categorization are better due to the fact that quantile categorization uses selected exact sample observations. On the other hand, frequency categorization is based on relative frequencies of intervals. For the last type of categorization, there are many samples with the same value at the test statistic, so its discrimination power is reduced.Research limitations/implicationsThe recommendation is limited to the power divergence test statistics introduced by Cressie and Read with parameter λ=−2,−1,−1/2,0,2/3,1,2 and several values of m and n.Practical implicationsAmong the two types of categorizations, quantile categorization is recommended for testing uniformity.Originality/valueThe paper gives useful recommendations to applied statisticians when testing for uniformity.

Suitability of mapped sequence tagged microsatellite site markers for establishing distinctness, uniformity and stability in aromatic rice

At present, testing for distinctness, uniformity and stability (DUS) of crop varieties relies on a set of morphological characters. These characters suffer fromthe limitations of number, interaction with the environment in which the variety grows and subjectivity in decision-making. The potential of DNA-based markers such as sequence tagged microsatellite site (STMS), for establishing DUS merits investigation. In the present study, a set of 55 mapped STMS markers, selected from 12 linkage groups of rice genome, was used to examine distinctness of 23 aromatic rice genotypes including the commercially important Basmati varieties. Forty-one of these markers (74.5%) showed polymorphism between the varieties. The number of alleles per locus ranged from 2–4 with an average of 2.3. The polymorphism information content (PIC) of the markers varied from 0.083 to 0.665 with an average of 0.338. All the varieties could be differentiated from each other at a low probability (0.07×10-13) of identical match by chance. The marker-based clustering of the varieties corresponded with the known phenotypic classification, thereby providing confidence in the distinctness established by the mapped STMS markers. The utility of these markers to study uniformity and stability was analysed using a commercially important crossbred Basmati rice variety Pusa Basmati 1(IET-10364) that contributes about 40–50% of Basmati rice export from India. Genotyping of twenty individual plants, grown from the nucleus, breeder, foundation, certified and farmer's saved seed samples using all the 55 markers revealed no variation among the plants. These observations suggested that the set of mapped markers employed in this study could be further used for establishing distinctness of aromatic rice varieties and for studying DUS of the important commercial variety Pusa Basmati 1.

Online quality control with Raman spectroscopy in pharmaceutical tablet manufacturing

Quality testing for tablet composition and uniformity at the manufacturing stage is critical to the pharmaceutical industry. However, current off-line, destructive, wet chemistry analysis incurs significant costs and long test times. This paper introduces a methodology to form a population batch size for quality control sampling in tablet manufacturing for an alternative online testing technology, Raman spectroscopy. An approach is presented to determine the minimum testing batch size for quality control sampling based on the desirable confidence level, margin of error, testing rate, and production rate. Experiments with both traditional wet chemistry analysis and Raman spectroscopy are conducted. The results demonstrate that the quality of Raman spectroscopy is comparable to that of wet chemistry analysis. The proposed quality sampling methodology reduces the queue time by orders of magnitude for typical tablet batches of one to four million tablets awaiting test results following the tablet compaction process. Furthermore, it increases the tablet sample size, which subsequently raises the confidence level.

Unit Dose Sampling and Final Product Performance: An Alternative Approach

This article documents a proposed plan for validation testing for the content uniformity for final blends and finished solid oral dosage forms (SODFs). The testing logic and statistical justification of the plan are presented. The plan provides good assurance that a passing lot will perform well against the USP tablet content uniformity test. The operating characteristics of the test and the probability of needing to test for blend sampling bias are reported. A case study is presented.