The sensitivity of measurement error in stand volume estimation

1990 ◽  
Vol 20 (6) ◽  
pp. 800-804 ◽  
Author(s):  
George Z. Gertner
Keyword(s):  
Measurement Error ◽  
Random Sample ◽  
Sampling Error ◽  
Regression Function ◽  
Volume Estimation ◽  
Simple Random Sample ◽  
Large Reduction ◽  
Stand Volume ◽  
Volume Function ◽  
Independent Variables

A method is given for approximating and evaluating the consequences of random and nonrandom errors in the independent variables of a nonlinear tree volume function that is used in the estimation of stand volume based on a simple random sample of plots. Sampling error, regression function error, and measurement error are accounted for with the method presented. An application is given where relatively moderate amounts of measurement error in the independent variables of a tree volume function can cause a relatively large reduction in the accuracy of estimated stand volume.

Variance reduction in Ueno's method and cylinder sampling for forest volume estimation

1995 ◽  
Vol 25 (11) ◽  
pp. 1783-1794 ◽  
Author(s):  
Thomas B. Lynch
Keyword(s):  
Computer Simulation ◽  
Variance Reduction ◽  
Volume Estimation ◽  
Critical Height ◽  
Volume Estimate ◽  
Individual Tree ◽  
Stand Volume ◽  
Reduction Techniques ◽  
Antithetic Variates ◽  
Volume Equation

Three basic techniques are proposed for reducing the variance of the stand volume estimate provided by cylinder sampling and Ueno's method. Ueno's method is based on critical height sampling but does not require measurement of critical heights. Instead, a count of trees whose critical heights are less than randomly generated heights is used to estimate stand volume. Cylinder sampling selects sample trees for which randomly generated heights fall within cylinders formed by tree heights and point sampling plot sizes. The methods proposed here for variance reduction in cylinder sampling and Ueno's method are antithetic variates, importance sampling, and control variates. Cylinder sampling without variance reduction was the most efficient of 12 methods compared in computer simulation that used estimated measurement times. However, cylinder sampling requires knowledge of a combined variable individual tree volume equation. Of the three variance reduction techniques applied to Ueno's method, antithetic variates performed best in computer simulation.

On Two Novel Applications of Ranked Set Sampling

2003 ◽  
Vol 54 (1-2) ◽  
pp. 105-114
Author(s):  
Sukuman Sarikavanij ◽  
Montip Tiensuw
Keyword(s):  
Case Studies ◽  
Random Sample ◽  
Ranked Set Sampling ◽  
Simple Random Sample ◽  
Single Family ◽  
Ranked Set Sample ◽  
Population Mean ◽  
Sales Data ◽  
Tree Data ◽  
Novel Applications

In this paper we discuss two case studies which clearly indicate the advantages of using a ranked set sample (RSS) over those of a simple random sample (SRS). The applications of RSS considered here cover single family homes sales data, and tree data. It is demonstrated that in each case RSS is much more efficient than SRS for estimation of population mean.

PREFERENSI PENGUNJUNG TERHADAP PELAYANAN DI GRHATAMA PUSTAKA YOGYAKARTA

Pringgitan ◽  
2020 ◽  
Vol 1 (02) ◽  
pp. 87-97
Author(s):  
Sabda Elisa Priyanto ◽  
Eko Sugiarto
Keyword(s):  
Service Quality ◽  
Random Sample ◽  
Sampling Method ◽  
Descriptive Study ◽  
Simple Random Sample ◽  
Library Services ◽  
Key Word ◽  
Recreation Area ◽  
Sample Technique ◽  
Visitor Preferences

The purpose of this paper is to describe the preferences of visitors to the service quality at Grhtama Pustaka Yogyakarta. The library has a function as a place of recreation that should be able to provide good services to visitors. The services provided must be based on visitor preferences when visiting and getting services. Visitor preferences for service quality that is tangible, reliability, responsiveness, assurance, and empathy. Grhtama Pustaka as the largest library in Yogyakarta must be able to provide good services, as a form of support to become a place of recreation in Yogyakarta.  The method in this research is a descriptive study, with a population of visitors to Grhatama Pustaka, selected by the probability sampling method with a simple random sample technique, by interviewing 118 visitors. The results of this study found that tourist preferences for services in Grhatama Pustaka in the tangible part are strong preferences for visitors to visit, while the reliability, responsiveness, assurance, and empathy factors in library services are good preferences for visitors who need library services. Furthermore, hospitality services are needed if the manager wants to make visitors make Grhatama Pustaka a choice of the recreation area. Key Word: Preference, Visitor, Service Quality, Library

On the Efficiency of Ranked Set Sampling Strategies in Parametric Estimation

1997 ◽  
Vol 47 (1-2) ◽  
pp. 23-42 ◽  
Author(s):  
Dayong Li ◽  
Nora Ni Chuiv
Keyword(s):  
Random Sample ◽  
Ranked Set Sampling ◽  
Parametric Estimation ◽  
Simple Random Sample ◽  
Sampling Strategies ◽  
Ranked Set Sample ◽  
Estimation Problems ◽  
Parameters Of Interest

In this paper we discuss the issue of efficiency of a ranked set sample compared to a simple random sample in the context of a variety of parametric estimation problems. We establish that the use of appropriate variations of a ranked set sample often results in improved estimation of many common parameters of interest with a substantially smaller number of measurements compared to a simple random sample.

scholarly journals A TOOL CONSTRUCTION AND STANDARDIZATION OF NUTRITION KNOWLEDGE OF HIGH SCHOOL STUDENTS

2017 ◽  
Vol 5 (5(SE)) ◽  
pp. 69-74
Author(s):  
T.Indumathi ◽  
N. Ramakrishnan
Keyword(s):  
High School ◽  
High School Students ◽  
Random Sample ◽  
Nutrition Knowledge ◽  
Simple Random Sample ◽  
School Students ◽  
Final Study ◽  
Sample Technique ◽  
Knowledge Scale

In the present study, Nutrition knowledge scale has been constructed and standardized of the High School Students. This scale consists of 54 statements. The simple random sample technique was used for this study. The sample consists of 50 High School Students are randomly selected from the Kancheepuram Districts. The ‘t’ value was sued to standardize the tool and finally 29 statements were retained for the final study.

scholarly journals Indigenous healers in the North West province: A survey of their clinical activities in health care in the rural areas

Curationis ◽  
1996 ◽  
Vol 19 (4) ◽  
Author(s):  
S. N. Shai-Mahoko
Keyword(s):  
Health Care ◽  
Random Sample ◽  
Southern Africa ◽  
Rural Areas ◽  
Demographic Variables ◽  
Simple Random Sample ◽  
North West ◽  
The North ◽  
Clinical Conditions

The purpose of this study was to explore the clinical conditions brought to indigenous healers by people in the rural areas in search of health care. The demographic variables and preventive, promotive, curative and follow-up activities of indigenous healers were investigated. Data were collected from a simple random sample of 35 indigenous healers. A questionnaire designed by Mogoba (1984) for investigation of training and functioning of traditional doctors in Southern Africa was modified and used to collect data.

How to improve allometric equations to estimate forest biomass stocks? Some hints from a central African forest

2014 ◽  
Vol 44 (7) ◽  
pp. 685-691 ◽  
Author(s):  
Quentin Moundounga Mavouroulou ◽  
Alfred Ngomanda ◽  
Nestor Laurier Engone Obiang ◽  
Judicaël Lebamba ◽  
Hugues Gomat ◽  
...  
Keyword(s):  
Measurement Error ◽  
Bayesian Model Averaging ◽  
Sampling Error ◽  
Forest Biomass ◽  
Model Averaging ◽  
Allometric Equation ◽  
Allometric Equations ◽  
Data Set ◽  
Equation Error ◽  
Source Of Error

Predicting the biomass of a forest stand using forest inventory data and allometric equations involves a chain of propagation of errors going from the sampling error to the tree measurement error. Using a biomass data set of 101 trees in a tropical rain forest in Gabon, we compared two sources of error: the error due to the choice of allometric equation, assessed using Bayesian model averaging, and the biomass measurement error when tree biomass is calculated from tree volume rather than directly weighed. Differences between allometric equations resulted in a between-equation error of about 0.245 for log-transformed biomass compared with a residual within-equation error of 0.297. Because the residual error is leveled off when randomly accumulating trees whereas the between-equation error is incompressible, the latter turned out to be a major source of error at the scale of a 1 ha plot. Measuring volumes rather than masses resulted in an error of 0.241 for log-transformed biomass and an average overestimation of the biomass by 19%. These results confirmed the choice of the allometric equation as a major source of error but unexpectedly showed that measuring volumes could seriously bias biomass estimates.

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