Use of crown ratio to improve loblolly pine taper equations

1986 ◽  
Vol 16 (5) ◽  
pp. 1141-1145 ◽  
Author(s):  
Michael A. Valenti ◽  
Quang V. Cao
Keyword(s):  
Test Data ◽  
Loblolly Pine ◽  
Data Set ◽  
Tree Form ◽  
Independent Variable ◽  
Taper Equation ◽  
Taper Equations ◽  
Better Than

Data from 278 trees felled in a loblolly pine (Pinustaeda L.) plantation were used to include crown ratio as a measure of tree form in a taper equation. The data were divided into 10 crown ratio classes. A segmented taper equation was fitted to each of the 10 classes to detect trends in the coefficients. Coefficients were then expressed as functions of crown ratio. The resulting three-segment taper equation with crown ratio as an additional independent variable was more flexible and provided more accurate predictions of upper stem diameters. Similar techniques were used to include crown ratio in a two-segment taper equation. The three-segment equation fitted the data better than the two-segment equation and provided superior taper predictions for the test data set.

scholarly journals A Taper Equation for Loblolly Pine Using Penalized Spline Regression

2021 ◽  
Vol 67 (1) ◽  
pp. 1-13
Author(s):  
Mauricio Zapata-Cuartas ◽  
Bronson P Bullock ◽  
Cristian R Montes
Keyword(s):  
Loblolly Pine ◽  
A Priori ◽  
Tree Height ◽  
Wood Products ◽  
Spline Regression ◽  
Tree Form ◽  
Penalized Spline ◽  
Taper Equation ◽  
Penalized Spline Regression ◽  
Taper Equations

Abstract Stem profile needs to be modeled with an accurate taper equation to produce reliable tree volume assessments. We propose a semiparametric method where few a priori functional form assumptions or parametric specification are required. We compared the diameter and volume predictions of a penalized spline regression (P-spline), P-spline extended with an additive dbh-class variable, and six alternative parametric taper equations including single, segmented, and variable-exponent equation forms. We used taper data from 147 loblolly pine (Pinus taeda L.) trees to fit the models and make comparisons. Here we show that the extended P-spline outperforms the parametric taper equations when used to predict outside bark diameter in the lower portion of the stem, up to 40% of the tree height where the more valuable wood products (62% of the total outside bark volume) are located. For volume, both P-spline models perform equal or better than the best parametric model, with taper calibration, which could result in possible savings on inventory costs by not requiring an additional measurement. Our findings suggest that assuming a priori fixed form in taper models imposes restrictions that fail to explain the tree form adequately compared with the proposed P-spline.

Tree Volume and Taper of Loblolly Pine Varies by Stand Origin

1987 ◽  
Vol 11 (4) ◽  
pp. 185-189 ◽  
Author(s):  
Ralph L. Amateis ◽  
Harold E. Burkhart
Keyword(s):  
Pinus Taeda ◽  
Loblolly Pine ◽  
Analysis Data ◽  
Old Field ◽  
Stem Analysis ◽  
Tree Form ◽  
Pinus Taeda L ◽  
Natural Stands ◽  
Taper Equations ◽  
Forest Managers

Abstract Stem analysis data were used to examine volume, height-dbh, form and taper relationships for loblolly pine (Pinus taeda L.) trees grown in unthinned old-field plantations, cutover-site plantations, and natural stands. Results showed significant differences in volume, height-dbh, tree form and taper relationships for loblolly pine grown in stands from these three origins. Thus, in order to accurately predict total and merchantable volumes as well as upper stem diameters and heights, forest managers should apply separate volume and taper equations for each stand class. South. J. Appl. For. 11(4):185-189.

scholarly journals Calibrating a Segmented Taper Equation with Two Diameter Measurements

2009 ◽  
Vol 33 (2) ◽  
pp. 58-61 ◽  
Author(s):  
Quang V. Cao
Keyword(s):  
Pinus Taeda ◽  
Loblolly Pine ◽  
Polynomial Regression ◽  
Stem Diameter ◽  
Laser Technology ◽  
Breast Height ◽  
Tree Data ◽  
Pinus Taeda L ◽  
Taper Equation ◽  
Taper Equations

Abstract Recent advances in laser technology help make possible accurate and affordable measurements of upper-stem diameters. These measurements can be used to calibrate results from a taper equation to improve the accuracy of diameter predictions along the tree bole. Felled-tree data from a loblolly pine (Pinus taeda L.) plantation were used to evaluate two methods for calibrating outputs from a segmented taper equation with parameters either obtained from the data in this study or originally published by <xref ref-type="bibr" rid="B5-2124">Max and Burkhart (1976</xref>, Segmented polynomial regression applied to taper equations, For. Sci. 22:283–289). For outside-bark diameters, although a simple calibration for dbh gave desirable results, a better calibration involving both dbh and an upper-stem diameter provided significant improvements in predicting tree taper. Results varied depending on where the diameter was measured, with optimum gains obtained when the upper-stem diameter was measured at the midpoint between breast height and the tree tip. For inside-bark diameters, the calibration for inside-bark dbh actually produced inferior predictions, whereas the calibration based on both dbh and an upper-stem diameter offered only modest improvements over the unadjusted predictions.

Segmented Quadratic Taper Equations for Spruce and Fir in the Northeast

1989 ◽  
Vol 6 (3) ◽  
pp. 123-126 ◽  
Author(s):  
Dale S. Solomon ◽  
Terry D. Droessler ◽  
Ronald C. Lemin
Keyword(s):  
Analysis Data ◽  
Red Spruce ◽  
Stem Analysis ◽  
Validation Data ◽  
Data Set ◽  
Error Analyses ◽  
Taper Equation ◽  
Taper Equations ◽  
Total Tree ◽  
Volume Equations

Abstract Segmented quadratic taper equations were developed from red spruce and balsam fir stem analysis data in the Northeast. Estimated diameters and volumes from the taper equations were compared with actual diameters and volumes in a validation data set, and were found to be precise and have negligible bias in prediction. The derived volume from the taper equation was also compared to existing total tree volume equations for spruce and fir. The error analyses showed the segmented taper equations provided an accurate and precise alternative to total tree volume equations. North. J. Appl. For. 6:123-126, September 1989.

Compatible taper equation for loblolly pine

1986 ◽  
Vol 16 (6) ◽  
pp. 1272-1277 ◽  
Author(s):  
J. P. McClure ◽  
R. L. Czaplewski
Keyword(s):  
Loblolly Pine ◽  
Volume Estimation ◽  
Main Stem ◽  
Stem Volume ◽  
Model Parameters ◽  
Data Set ◽  
Fit Statistics ◽  
Estimation Formula ◽  
Volume Equation ◽  
Taper Equation

Cao's compatible, segmented polynomial taper equation (Q. V. Cao, H. E. Burkhart, and T. A. Max. For. Sci. 26: 71–80. 1980) is fitted to a large loblolly pine data set from the southeastern United States. Equations are presented that predict diameter at a given height, height to a given top diameter, and volume below a given position on the main stem. All estimates are inside bark. A condition is given that forces the Cao model to be exactly compatible with any total main stem volume equation. An exact volume estimation formula is derived. Twelve benchmarks, which represent realistic utilization criteria, are used to describe expected errors in actually applying the taper equation rather than the more common fit statistics that describe errors encountered when estimating model parameters. Errors in using the fitted model are very similar to errors using Cao's estimates.

Dimensionally compatible volume and taper equations

2001 ◽  
Vol 31 (5) ◽  
pp. 797-803 ◽  
Author(s):  
Mahadev Sharma ◽  
Richard G Oderwald
Keyword(s):  
North Carolina ◽  
Loblolly Pine ◽  
Coastal Plain ◽  
Pine Trees ◽  
Volume Equation ◽  
Pinus Taeda L ◽  
Taper Equation ◽  
Natural Stands ◽  
Taper Equations ◽  
Volume Equations

A dimensional analysis approach was applied to derive analytically consistent tree taper and volume equations. To achieve numerical consistency between the taper and volume equations, parameters of the taper and the volume equations were estimated simultaneously. Data from loblolly pine (Pinus taeda L.) trees grown in natural stands in the Coastal Plain of North Carolina and the Coastal Plain and Piedmont areas of Virginia were used to estimate the parameters. The dimensionally compatible volume equation is shown to be a better equation for estimation of the volume of loblolly pine trees grown in these sites and can be applied for the estimation of total volume. The taper equation accurately predicts tree diameters from butt to the tree tip. It can be used to predict the diameter at any specified height and to predict height to any top diameter limit.

Pemberian Umpan Balik Dalam Meningkatkan Hasil Belajar dan Minat Belajar Mahasiswa

2015 ◽  
Vol 4 (3) ◽  
Author(s):  
Seruni Seruni ◽  
Nurul Hikmah
Keyword(s):  
Information Technology ◽  
Learning Outcomes ◽  
Test Data ◽  
Random Sampling ◽  
Covariance Matrices ◽  
Test Results ◽  
Immediate Feedback ◽  
Statistics Course ◽  
Independent Variable ◽  
Descriptive Statistical Analysis

<p>The purpose of this study is to find and analyze the effect of feedback on <br />learning outcomes in mathematics and an interest in basic statistics course. The <br />population in this study are affordable Information Technology Student cademic Year 2012/2013 Semester II Indraprasta PGRI University of South Jakarta. Sample The study sample was obtained through random sampling. This study used an experimental method to the analysis using the MANOVA test. This study has three variables, consisting of: one independent variable, namely the provision of feedback (immediate and delayed), and two dependent variable is the result of interest in the study of mathematics and basic statistics course. The data was collected for the test results to learn mathematics, and a questionnaire for the interest in basic statistics course. Collected data were analyzed using the MANOVA test. Before the data were analyzed, first performed descriptive statistical analysis and test data analysis requirements (test data normality and homogeneity of covariance matrices). The results show that the learning outcomes of interest in mathematics and basic statistics course for students who are given immediate feedback higher than students given feedback delayed. <br /><br /></p>

Evaluation for estimating of the PDF and the CDF of Generalized Inverted Exponential Distribution with Application in Industry

2020 ◽  
pp. 507-522
Author(s):  
Parisa Torkaman
Keyword(s):  
Least Squares ◽  
Exponential Distribution ◽  
Mean Squared Error ◽  
Weighted Least Squares ◽  
Real Data ◽  
Minimum Variance ◽  
Cumulative Distribution ◽  
Estimation Methods ◽  
Data Set ◽  
Better Than

The generalized inverted exponential distribution is introduced as a lifetime model with good statistical properties. This paper, the estimation of the probability density function and the cumulative distribution function of with five different estimation methods: uniformly minimum variance unbiased(UMVU), maximum likelihood(ML), least squares(LS), weighted least squares (WLS) and percentile(PC) estimators are considered. The performance of these estimation procedures, based on the mean squared error (MSE) by numerical simulations are compared. Simulation studies express that the UMVU estimator performs better than others and when the sample size is large enough the ML and UMVU estimators are almost equivalent and efficient than LS, WLS and PC. Finally, the result using a real data set are analyzed.

A Computational Method for the Identification of Endolysins and Autolysins

2020 ◽  
Vol 27 (4) ◽  
pp. 329-336 ◽  
Author(s):  
Lei Xu ◽  
Guangmin Liang ◽  
Baowen Chen ◽  
Xu Tan ◽  
Huaikun Xiang ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Cell Wall ◽  
Experimental Results ◽  
Computational Method ◽  
Lytic Enzyme ◽  
Support Vector ◽  
Lytic Enzymes ◽  
Data Set ◽  
Optimal Feature ◽  
Better Than

Background: Cell lytic enzyme is a kind of highly evolved protein, which can destroy the cell structure and kill the bacteria. Compared with antibiotics, cell lytic enzyme will not cause serious problem of drug resistance of pathogenic bacteria. Thus, the study of cell wall lytic enzymes aims at finding an efficient way for curing bacteria infectious. Compared with using antibiotics, the problem of drug resistance becomes more serious. Therefore, it is a good choice for curing bacterial infections by using cell lytic enzymes. Cell lytic enzyme includes endolysin and autolysin and the difference between them is the purpose of the break of cell wall. The identification of the type of cell lytic enzymes is meaningful for the study of cell wall enzymes. Objective: In this article, our motivation is to predict the type of cell lytic enzyme. Cell lytic enzyme is helpful for killing bacteria, so it is meaningful for study the type of cell lytic enzyme. However, it is time consuming to detect the type of cell lytic enzyme by experimental methods. Thus, an efficient computational method for the type of cell lytic enzyme prediction is proposed in our work. Method: We propose a computational method for the prediction of endolysin and autolysin. First, a data set containing 27 endolysins and 41 autolysins is built. Then the protein is represented by tripeptides composition. The features are selected with larger confidence degree. At last, the classifier is trained by the labeled vectors based on support vector machine. The learned classifier is used to predict the type of cell lytic enzyme. Results: Following the proposed method, the experimental results show that the overall accuracy can attain 97.06%, when 44 features are selected. Compared with Ding's method, our method improves the overall accuracy by nearly 4.5% ((97.06-92.9)/92.9%). The performance of our proposed method is stable, when the selected feature number is from 40 to 70. The overall accuracy of tripeptides optimal feature set is 94.12%, and the overall accuracy of Chou's amphiphilic PseAAC method is 76.2%. The experimental results also demonstrate that the overall accuracy is improved by nearly 18% when using the tripeptides optimal feature set. Conclusion: The paper proposed an efficient method for identifying endolysin and autolysin. In this paper, support vector machine is used to predict the type of cell lytic enzyme. The experimental results show that the overall accuracy of the proposed method is 94.12%, which is better than some existing methods. In conclusion, the selected 44 features can improve the overall accuracy for identification of the type of cell lytic enzyme. Support vector machine performs better than other classifiers when using the selected feature set on the benchmark data set.

How to Assess Prognostic Models for Survival Data: A Case Study in Oncology

2003 ◽  
Vol 42 (05) ◽  
pp. 564-571 ◽  
Author(s):  
M. Schumacher ◽  
E. Graf ◽  
T. Gerds
Keyword(s):  
Test Data ◽  
Survival Data ◽  
Prediction Error ◽  
Classification Scheme ◽  
Neural Nets ◽  
Brier Score ◽  
Data Set ◽  
Independent Test ◽  
Artificial Neural

Summary Objectives: A lack of generally applicable tools for the assessment of predictions for survival data has to be recognized. Prediction error curves based on the Brier score that have been suggested as a sensible approach are illustrated by means of a case study. Methods: The concept of predictions made in terms of conditional survival probabilities given the patient’s covariates is introduced. Such predictions are derived from various statistical models for survival data including artificial neural networks. The idea of how the prediction error of a prognostic classification scheme can be followed over time is illustrated with the data of two studies on the prognosis of node positive breast cancer patients, one of them serving as an independent test data set. Results and Conclusions: The Brier score as a function of time is shown to be a valuable tool for assessing the predictive performance of prognostic classification schemes for survival data incorporating censored observations. Comparison with the prediction based on the pooled Kaplan Meier estimator yields a benchmark value for any classification scheme incorporating patient’s covariate measurements. The problem of an overoptimistic assessment of prediction error caused by data-driven modelling as it is, for example, done with artificial neural nets can be circumvented by an assessment in an independent test data set.

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