Feb 15, 2018 · Maximum likelihood estimation or otherwise noted as MLE is a popular mechanism which is used to estimate the model parameters of a regression model. Other than regression, it is very often used in…
The residuals assessed then are either the Pearson residuals, studentized Pearson residuals, and/or the deviance residuals. A plot that is helpful for diagnosing logistic regression model is to plot the studentized Pearson residuals, or the deviance residuals, against the estimated probability or linear predictor values with a Lowess smooth.
Consequently, they calculate the correlation coefficient r, a p value for its significance testing and a regression line with an 80 percent confidence interval (Figure 8.2). Using the slope of each of the regression lines they calculate the speed and spread of the Gravettian techno-complex.
3.8.1 Pearson Residuals A very simple approach to the calculation of residuals is to take the difference between observed and fitted values and divide by an estimate of the standard deviation of the observed value. The resulting residual has the form (3.15) p i = y i − μ ^ i μ ^ i (n i − μ ^ i) / n i,