Sequential Sampling Method Research Articles

Method for sequential sampling of cerebrospinal fluid in humans

The authors describe a method for sequential cerebrospinal fluid sampling in humans by modifying the technique for continuous lumbar drainage. (Neurosurgery 23:788-790, 1988)

Soil nitrogen supply of wheat in relation to method of cultivation

The supply of soil nitrogen to successive wheat crops was compared for direct-drilled and conventional tillage systems on a red earth in south-eastern Australia. There was no significant effect of tillage on the total plant uptake of nitrogen, nor on the decline of soil nitrogen during a 5-year cropping cycle. During the growth of the last two crops in the cycle, the rates of net mineralization, nitrate leaching from the topsoil and crop-nitrogen uptake were measured, for both tillage systems, by an in situ sequential sampling method. For the first of these crops the rates of net mineralization were unaffected by tillage, but for the second crop the rates were greater on the direct-drilled soil. Variation in the rates of mineralization within both seasons could largely be explained by changes in temperature and soil water content. Leaching of nitrate from the topsoil was consistently greater for the direct-drilled soil, where seedlings initially accumulated less nitrogen than those growing on conventionally-cultivated soil. However, the differences in uptake did not persist, and at maturity similar amounts of nitrogen, representing less than 50% of the seasonal net mineralization, were accumulated in the above-ground parts of crops grown under the two systems.

Monte Carlo simulation of uncertainties in three-count total alpha radon progeny measurement techniques

Abstract Recent studies of three-count total alpha sequential sampling and counting methods using a law of propagation of errors (LPE) model have shown that small variations in pump flow rate and airborne radon progeny concentrations present from measurement to measurement can result in much larger variations in the overall precision of measurement than can be predicted on the basis of counting statistics alone. In contrast, results predicted by a Monte Carlo simulation (MCS) model develop in this work show that these variations have only a small effect on the overall precision of measurement for radon progeny concentrations typically found in uranium mines (1000–3700 Bq m −3 ) and in buildings with potential alpha energy concentrations equal to or exceeding 4 × 10 −7 J m −3 (0.02 WL). The discrepancy observed between results predicted by the MCS model and the LPE model is attributed mainly to the LPE model assumption of independence of variations in alpha count totals and independence of variations in estimated airborne radon progeny concentrations. For the case where radioactive decay is the only source of random error, the LPE model assumption of independence in estimated airborne radon progeny concentrations results in an overestimation of the relative standard deviation of the potential alpha energy concentration by from 80 to 105%. Monte Carlo precision estimates evaluated for sequential three-count total-alpha measurement techniques show that precision estimates based on counting statistics alone are reliable when measurement to measurement pump flow rate variations are less than 3% and litre to litre concentration variations are less than 10%. This result is valid for radon progeny concentrations typically found in uranium mines. When sampling is performed to monitor radon progeny concentrations in houses with potential alpha energy concentrations equal to or exceeding 4 × 10 −7 J m −3 , the range over which precision estimates based on counting statistics alone are reliable can be extended to measurement to measurement pump flow rate variations of 10% and litre to litre concentration variations of 50%.

A Bayesian Method for Sequential Sampling and Forecasting in Agricultural Pest Management

SUMMARY We present a method for sequential estimation of the state of infestation of an agricultural crop by a pest arthropod. The method, which is based on Bayesian statistical theory, establishes stopping curves by requiring that a confidence interval be placed entirely on one side or the other of an economic threshold. The results of a given sequential sample are used to modify the prior of the subsequent sample by assuming that the infestation follows a particular growth law. The parameters of this growth law are themselves uncertain and are described by subjective distributions that are modified by the sampling. A major advantage of our method is that it readily admits the incorporation of a forecasting scheme. After describing the development of the method in general terms, we give a specific example of the application of the method to the sampling of spider mites on cotton in the

Bean Leaf Beetle 1 : Micro-Spatial Patterns and Sequential Sampling of Field Populations 2

Dispersion of teneral and mature bean leaf beetles (BLB) populations approximated a negative binomial with the single individual being the basic component of the distribution. Aggregation indices indicated departure from randomness but only a slight degree of clumping. The common k of the negative binomial was distinctly lower for callow BLB than for mature BLB. The degree of aggregation of mature BLB was correlated with the seasonal fluctuations in abundance of the callow BLB. It is suggested that the ovipositing behavior of females is the causative factor of subsequent BLB aggregation. Using sampling decision rules for adult BLB based on Morisita's I∂ and Lloyd's coefficients, 30–50 random samples of 20 sweeps adequately estimate BLB densities in homogeneous soybean fields. Simple sequential sampling methods suited to ecological population studies and estimation of population levels in relation to a predetermined threshold are suggested.

A new method of sequential sampling to classify populations relative to a critical density

SummaryA method of sequential sampling for grading population level in relation to a critical density is proposed. The method is based on the relationship and can be used without restrictions on the distribution patterns. The formulae for simple random sampling as well as for two‐stage sampling are given.

Applicability of a New Sequential Sampling Method in the Field Population Surveys

Applicability of a New Sequential Sampling Method in the Field Population Surveys

White Spruce Cone Production and Prediction of Cone Crops

In September preceding the seed year, reproductive buds of white spruce can be recognized with the naked eye. The numbers of ovulate buds are a good indication of the prospective cone crop. A method of sequential sampling on a small number of trees, which enables a prediction of cone crop potential on a stand or regional basis, is presented. This advance information facilitates planning of seedbed preparation for natural regeneration, seed collection and artificial reforestation.

SEQUENTIAL SAMPLING FOR EGG CLUSTERS OF THE SWAINE JACK PINE SAWFLY, NEODIPRION SWAINEI (HYMENOPTERA: DIPRIONIDAE)

AbstractA sequential sampling method for egg clusters of the Swaine jack pine sawfly, Neodiprion swainei Middleton, is described.

A new method of sequential sampling to obtain the population estimates with a fixed level of precision

SummaryA simple method of sequential sampling is developed which would make it automatically possible to secure, without excess sampling, a predetermined level of precision for a series of population estimates being required. It appears to have wide application to sampling field populations under various situations since it is simply based upon the relationship of variance to mean for which a comprehensive formula deduced for biological populations from the linearity in the regression of mean crowding on mean density could be adopted. Some problems that may arise in practical application of the method are also discussed.

Sequential Sampling for White Grubs

Abstract>The results of sampling to determine the vertical distribution of white grubs in the soil and the frequency distribution of grubs per 1-square-foot sample unit are presented. It was found that the optimum sampling period is during June and July, when most of the grubs are in the upper foot of soil. The negative binomial distribution with a k value of 1.5936 fitted most of the data well and was used to devise two sequential sampling methods: one for classifying white grub populations as light, moderate or severe; the other for pre-planting surveys to determine whether or not control measures are required.

Sequential Tests for Variance Ratios and Components of Variance

A general sequential sampling method is given for problems of comparing the variances of two or more normal populations in terms of ratios of variances. Sequential tests are given for a hypothesis specifying the ratio of two variances, including tests for variance components in the analysis of variance (Model II). Such tests provide savings in average required numbers of observations, relative to standard F tests, comparable to those typical of sequential probability ratio tests.

A Sequential Sampling Technique for Surveys of the Larch Sawfly

Sequential sampling methods have been developed for population surveys of a number of forest insects (4, 6, 7, 9). These methods permit rapid classification of populations into broad infestation classes with predetermined accuracy and a minimum of sampling, and are useful for mapping and recording widespread infestations.The method of assessing egg populations of the larch sawfly, Pristiphora erichsonii (Htg.), developed by Ives (3) for intensive population studies, was not suitable for surveys because of the large sample size required. A sequential plan for the larch sawfly using hypothetical infestation classes was briefly reviewed by Ives (2). This plan is modified in the present paper in accordance with new data that have accumulated from observations on plots in the Whiteshell Forest Reserve and other stands in Manitoba and Saskatchewan.

Methods of Deferred Sentencing in Testing the Fraction Defective of a Continuous Output

Summary When the output of a continuous process is subjected to a routine test, in which it is observed whether the articles sampled are satisfactory or defective, a clustering of defectives (i.e. the occurrence of several defectives in rapid succession) may be taken as an indication that quality has deteriorated. In Part I inspection schemes of this kind are considered and compared with sequential sampling methods applied to the product after it has been divided into bulks of a suitable size. In Part II it is shown how the operating characteristic of a deferred sentencing scheme can be calculated. These schemes are, we believe, the only inspection procedures available at present that relate specifically to a continuous output and apply when the inspection test is destructive. They are non-rectifying. Mathematically, we are concerned with, among other problems, the frequency of clusters of random points on a line of infinite length. Most of the work on which this paper is based was carried out by the authors in the Ministry of Supply Advisory Service on Statistical Method (S.R. 17), and their thanks are due to the Director-General of Scientific Research (Defence) for permission to publish it. Part I and the first section of Part II are by F. J. Anscombe, and the remainder of Part II by H. J. Godwin and R. L. Plackett, as indicated by author’s initials.