TIMBER SAMPLING AND ANALYSIS
Tags: SAMPLE variance; TIMBER; SAMPLING (Statistics); MOISTURE; SAWING
Related Articles
- On conditional sampling strategies. Wywial, Janusz // Statistical Papers;Jul2003, Vol. 44 Issue 3, p397
Estimation of the population average by means of a conditional strategy has been considered e.g. in [2-6,9] and [10]. Let us assume that the sampling design depends on a function of an auxiliary variable called an auxiliary statistic like: the sample mean or the sample variance. Under the...
- Influence functions and robust Bayes and empirical Bayes small area estimation. Malay Ghosh; Tapabrata Maiti; Ananya Roy // Biometrika;Sep2008, Vol. 95 Issue 3, p573
We introduce new robust small area estimation procedures based on area-level models. We first find influence functions corresponding to each individual area-level observation by measuring the divergence between the posterior density functions of regression coefficients with and without that...
- LIVE FUEL MOISTURE SAMPLING METHODS: A COMPARISON. Brown, Annie; Omi, Philip N.; Pollet, Jolie // Fire Management Today;Fall2009, Vol. 69 Issue 4, p37
The article presents a study on live fuel moisture (LFM) sampling methods. It defines LFM content as influencing fire behavior in fuel types dominated by living vegetation describing collection procedures which combined 3 variables for comparison and performed a statistical analysis of the...
- A New Way of Looking at Sampling Errors and Data Variation. Smith, Patricia L. // Journal of GXP Compliance;Summer2009, Vol. 13 Issue 3, p75
The article discusses a way of looking at sampling errors and data variation. Careful and thorough evaluation and analysis of potential sampling errors is a way to enhance the evaluation of suspect data. It notes that material, process, sampling, and laboratory contribute to variation in final...
- Model for small-sample bias of free-energy calculations applied to Gaussian-distributed nonequilibrium work measurements. Wu, Di; Kofke, David A. // Journal of Chemical Physics;11/8/2004, Vol. 121 Issue 18, p8742
We present a model for the bias of free-energy differences when determined using the nonequilibrium work (NEW) formalism due to Jarzynski. Input to the model is the distribution of work values underlying the NEW calculation, and the bias is estimated by assuming that all of the inaccuracy is...
- Optimal sampling schemes based on the anticipated variance with lack of fit. Mandallaz, D. // Canadian Journal of Forest Research;Dec2002, Vol. 32 Issue 12, p2236
Presents an important improvement for optimal sampling schemes based on the anticipated variance. How the anticipated variance is defined as the average of the design-based variance under a simple stochastic model in which the trees are assumed to be uniformly and independently distributed...
- Estimation of a normal mean relative to balanced loss functions. Farsipour, N. Sanjari; Asgharzadeh, A. // Statistical Papers;Apr2004, Vol. 45 Issue 2, p279
Let X1 ..., Xn be a random sample from a normal distribution with mean ? and variance &sigma�. The problem is to estimate ? with Zellner's (1994) balanced loss function, LB (?, ?) = ?/n S1n (Xi - ?)� + (1 - ?)(? - ?)�, where 0 < ? < 1. It is shown that the sample mean Arithmetic means of...
- Ratio Type Estimators of the Population Mean Based on Ranked Set Sampling. Al-Hadhrami, Said Ali // World Academy of Science, Engineering & Technology;Nov2009, Vol. 59, p316
Ranked set sampling (RSS) was first suggested to increase the efficiency of the population mean. It has been shown that this method is highly beneficial to the estimation based on simple random sampling (SRS). There has been considerable development and many modifications were done on this...
- Sampling Almonds for Aflatoxin, Part I: Estimation of Uncertainty Associated with Sampling, Sample Preparation, and Analysis. Whitaker, Thomas B.; Slate, Andrew B.; Jacobs, Merle; Hurley, J. Michael; Adams, Julie G.; Giesbrecht, Francis G. // Journal of AOAC International;Jul/Aug2006, Vol. 89 Issue 4, p1027
The article the investigates the uncertainty associated with sampling lots of shelled almonds for aflatoxin to evaluate the performance of aflatoxin sampling plans. The total variance associated with measuring B1 and total aflatoxins in bulk almond lots was estimated and partitioned into...
