After using model selection to determine whether hybridization or adaptation to abiotic conditions at site origins was more important in predicting plant growth traits, we then employed mixed-model analysis of covariance (ancova) for the investigation of defoliation damage and plant performance measurements using the statistical program JMP v9.0.2 (SAS Institute, Cary NC, USA).
It should be noted that a new compensation scheme is introduced to improve the estimation performance by properly using the statistical property of the imperfect measurements.
Here we present (i) An approach for the automated extraction of urban areas from Landsat imagery using GEE, validated using higher resolution images, (ii) a novel method of validation of the extracted urban extents using changes in the statistical performance of a high resolution population mapping method.
A Markov chain methodology is used to evaluate the statistical performance of these charts.
Learning curve, i.e., plotting the mean square error (MSE) against the number of iterations, can be used to measure the statistical performance of adaptive algorithms [1, 2].
Our analytical model can be used to evaluate the statistical performance of DCF in realistic WLAN environments since it takes more factors into account including the finite retransmission limit, the probability that the backoff counter is frozen when the channel is sensed busy, error-prone channels, and multiple data rates.
Further, the results from the item analyses were to be used to comment on the statistical performance of the FSEP assessment forms as a whole, particularly with regard to Rasch model fit and measures of test reliability.
The proposed approach uses a Markov chain approach to compute the statistical performance, and uses a statistical design model to design DSVSI ¯¯¯X and s charts for detecting the mean shift and variance increase.
Wade and Woodall (1993) proposed using prediction limits to improve the statistical performance of cause-selecting control charts.
The statistical performance of each model was assessed using logistic regression [ 9].
