60 citations · 234 across the 39 of their papers we have counts for
16 papers · 1 filter
Measuring multi-calibration
Ido Guy, Daniel Haimovich, Fridolin Linder +4
A suitable scalar metric can help measure multi-calibration, defined as follows. When the expected values of observed responses are equal to corresponding predicted probabilities,…
Cumulative differences between subpopulations versus body mass index in the Behavioral Risk Factor Surveillance System data
Mark Tygert
Prior works have demonstrated many advantages of cumulative statistics over the classical methods of reliability diagrams, ECEs (empirical, estimated, or expected calibration error…
Cumulative differences between paired samples
Isabel Kloumann, Hannah Korevaar, Chris McConnell +2
The simplest, most common paired samples consist of observations from two populations, with each observed response from one population corresponding to an observed response from th…
Ties in ranking scores can be treated as weighted samples
Mark Tygert
Prior proposals for cumulative statistics suggest making tiny random perturbations to the scores (independent variables in a regression) in order to ensure the scores' uniqueness.…
Calibration of P-values for calibration and for deviation of a subpopulation from the full population
Mark Tygert
The author's recent research papers, "Cumulative deviation of a subpopulation from the full population" and "A graphical method of cumulative differences between two subpopulations…
A graphical method of cumulative differences between two subpopulations
Mark Tygert
Comparing the differences in outcomes (that is, in "dependent variables") between two subpopulations is often most informative when comparing outcomes only for individuals from the…
Cumulative deviation of a subpopulation from the full population
Mark Tygert
Assessing equity in treatment of a subpopulation often involves assigning numerical "scores" to all individuals in the full population such that similar individuals get similar sco…
Plots of the cumulative differences between observed and expected values of ordered Bernoulli variates
Mark Tygert
Many predictions are probabilistic in nature; for example, a prediction could be for precipitation tomorrow, but with only a 30 percent chance. Given both the predictions and the a…
Regression-aware decompositions
Mark Tygert
Linear least-squares regression with a "design" matrix A approximates a given matrix B via minimization of the spectral- or Frobenius-norm discrepancy ||AX-B|| over every conformin…
Testing goodness-of-fit for logistic regression
Mark Tygert, Rachel Ward
Explicitly accounting for all applicable independent variables, even when the model being tested does not, is critical in testing goodness-of-fit for logistic regression. This can…
Significance testing without truth
William Perkins, Mark Tygert, Rachel Ward
A popular approach to significance testing proposes to decide whether the given hypothesized statistical model is likely to be true (or false). Statistical decision theory provides…
A comparison of the discrete Kolmogorov-Smirnov statistic and the Euclidean distance
Jacob Carruth, Mark Tygert, Rachel Ward
Goodness-of-fit tests gauge whether a given set of observations is consistent (up to expected random fluctuations) with arising as independent and identically distributed (i.i.d.)…
An introduction to how chi-square and classical exact tests often wildly misreport significance and how the remedy lies in computers
William Perkins, Mark Tygert, Rachel Ward
Goodness-of-fit tests based on the Euclidean distance often outperform chi-square and other classical tests (including the standard exact tests) by at least an order of magnitude w…
Testing the significance of assuming homogeneity in contingency-tables/cross-tabulations
Mark Tygert
The model for homogeneity of proportions in a two-way contingency-table/cross-tabulation is the same as the model of independence, except that the probabilistic process generating…
Chi-square and classical exact tests often wildly misreport significance; the remedy lies in computers
William Perkins, Mark Tygert, Rachel Ward
If a discrete probability distribution in a model being tested for goodness-of-fit is not close to uniform, then forming the Pearson chi-square statistic can involve division by ne…
Statistical tests for whether a given set of independent, identically distributed draws does not come from a specified probability density
Mark Tygert
We discuss several tests for whether a given set of independent and identically distributed (i.i.d.) draws does not come from a specified probability density function. The most com…