4, December, 2023

i worked on the following tests and plots:

1.Standardized Residual Plot:

    • This plot displays the standardized residuals of the model over time.
    • Residuals are the differences between observed and predicted values.
    • Ideally, residuals should fluctuate randomly around zero, without any discernible pattern.
    • In our plot, we observed a fairly random scatter of residuals, although there are some instances of potential outliers.
  1. Histogram and Estimated Density Plot:
    • The histogram bins the standardized residuals to show their distribution.
    • An overlaid kernel density estimate (KDE) shows a smoothed version of this distribution.
    • A standard normal distribution (N(0,1)) is plotted for comparison.
    • A good-fitting model would have residuals that closely follow a normal distribution. The histogram should resemble the bell shape of the normal distribution curve.
  2. Normal Q-Q Plot:
    • The quantile-quantile plot compares the quantiles of the residuals with the quantiles of a normal distribution.
    • If the residuals are normally distributed, the points should fall approximately along the red line.
    • In the plot, the points largely follow the line, suggesting normality, but deviations at the ends may indicate heavier tails than the normal distribution.
  3. Correlogram (ACF Plot):
    • The correlogram, or autocorrelation function plot, shows the correlation of the residuals with themselves at different lags.
    • We look for correlations that are significantly different from zero at various lag intervals.
    • In a well-fitted model, we expect that there will be no significant autocorrelation in the residuals. Here, most autocorrelations are within the confidence band, indicating no significant autocorrelation.

Leave a Reply

Your email address will not be published. Required fields are marked *