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A note on robust estimation in logistic regression model

100%
Bednarski T.
Discussiones Mathematicae Probability and Statistics
|
2016
|
tom 36
|
nr 1-2
43-51
EN
Computationally attractive Fisher consistent robust estimation methods based on adaptive explanatory variables trimming are proposed for the logistic regression model. Results of a Monte Carlo experiment and a real data analysis show its good behavior for moderate sample sizes. The method is applicable when some distributional information about explanatory variables is available.
2
Content available remote

An evaluation of the efficiency of plant protection products via nonlinear statistical methods – a simulation study

80%
Skotarczak E., Bakinowska E., Tomaszyk K.
Biometrical Letters
|
2014
|
tom 51
|
nr 2
171-179
EN
A nonlinear statistical approach was used to evaluate the efficiency of plant protection products. The methodology presented can be implemented when the observations in an experiment are recorded as success or failure. This occurs, for example, when following the application of a herbicide or pesticide, a single weed or insect is classified as alive (failure) or dead (success). Then a higher probability of success means a higher efficiency of the tested product. Using simulated data sets, a comparison was made of three methods based on the logit, probit and threshold models, with special attention to the effect of sample size and number of replications on the accuracy of the estimation of probabilities.
3
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Impact of cereal diseases on the qualitative traits of spring barley breeding lines

61%
Zawieja B., Bakinowska E., Bichoński A., Pilarczyk W.
Biometrical Letters
|
2017
|
tom 54
|
nr 1
77-90
EN
The differences between individual breeding lines of spring barley and a control variety were tested in terms of several measured (continuous) and qualitative traits. The impact of the qualitative traits (diseases) on the quantitative traits, especially yield, was assessed on the basis of the significance of differences for both qualitative traits and yield. Depending on the type of trait, either a logistic model or analysis of variance was used as a statistical tool. The statistically significant differences between some breeding lines and the control variety were shown. It was observed that in fodder barley both infection by mildew and lodging influenced yield. The results of analyses obtained in the so-called pre-preliminary trials and preliminary trials were different. This fact confirmed the necessity of repeating trials over several years.
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