Probability plots are popular and effective tools for the graphical assessment of the goodness-of-fit of a given dataset to a hypothesised probability distribution, F say, with density f. The user can easily see any departures from F that there are, but the interpretation of such departures may not be immediately apparent. (It may take some time to work out their meaning, or else to resort to a set of rules for the interpretation of probability plots.) We investigate whether instant interpretability of these tools can be aided by a simple transformation which transfers visual assessment to the realms of familiar and immediate comparisons between densities. We seek to do so without smoothing, and see how far this allows us to go. The idea is...
An ability to understand the outputs of data analysis is a key characteristic of data literacy and t...
A plot for comparing two probability distributions, usually the sample distribution function and a t...
Whilst many numeric methods, such as AIC and deviance, exist for assessing or comparing model fit, d...
Probability plots are popular and effective tools for the graphical assessment of the goodness-of-fi...
Density probability plots show two guesses at the density function of a continuous variable, given a...
Assessing the distributional assumptions about univariate and multivariate data is a basic concern i...
We propose a user-friendly graphical tool, the half-disk density strip (HDDS), for visualizing and c...
Effective graphical presentation efficiently summarizes, ex-poses, and communicates patterns in data...
Background Results of probabilistic sensitivity analyses (PSA) are frequently visualized as a scatte...
This paper describes and discusses graphical techniques, based on the primitive empirical cumulative...
Background: Results of probabilistic sensitivity analyses (PSA) are frequently visualized as a scatt...
Probability plots are widely used tools for assessing distributional assumptions, but accurate inter...
Normal probability plots are widely used as a statistical tool for assessing whether an observed sim...
Probability density estimation from data is a widely studied problem. Often, the primary goal is to ...
Density maps allow for visually rendering density differences, usually mapping density values to a g...
An ability to understand the outputs of data analysis is a key characteristic of data literacy and t...
A plot for comparing two probability distributions, usually the sample distribution function and a t...
Whilst many numeric methods, such as AIC and deviance, exist for assessing or comparing model fit, d...
Probability plots are popular and effective tools for the graphical assessment of the goodness-of-fi...
Density probability plots show two guesses at the density function of a continuous variable, given a...
Assessing the distributional assumptions about univariate and multivariate data is a basic concern i...
We propose a user-friendly graphical tool, the half-disk density strip (HDDS), for visualizing and c...
Effective graphical presentation efficiently summarizes, ex-poses, and communicates patterns in data...
Background Results of probabilistic sensitivity analyses (PSA) are frequently visualized as a scatte...
This paper describes and discusses graphical techniques, based on the primitive empirical cumulative...
Background: Results of probabilistic sensitivity analyses (PSA) are frequently visualized as a scatt...
Probability plots are widely used tools for assessing distributional assumptions, but accurate inter...
Normal probability plots are widely used as a statistical tool for assessing whether an observed sim...
Probability density estimation from data is a widely studied problem. Often, the primary goal is to ...
Density maps allow for visually rendering density differences, usually mapping density values to a g...
An ability to understand the outputs of data analysis is a key characteristic of data literacy and t...
A plot for comparing two probability distributions, usually the sample distribution function and a t...
Whilst many numeric methods, such as AIC and deviance, exist for assessing or comparing model fit, d...