In summary, the error message "Cannot compute confidence intervals if #observations<=#coefficients" arises from the mathematical principles and assumptions used in statistical inference. It highlights the need for a sufficient number of observations to estimate the variability of coefficients accurately and compute reliable confidence intervals.
The error message you are seeing indicates that there are fewer observations (data points) than the number of coefficients in your model. Confidence intervals cannot be computed in this case because there is not enough data to estimate the variability of the coefficients.
To resolve this issue, you have a few options:
1. Increase the number of observations: If possible, collect more data points to increase the number of observations. This will provide more information for estimating the coefficients and allow for the computation of confidence intervals.
2. Simplify the model: If your model has a large number of coefficients, consider simplifying it by reducing the number of predictors or using a simpler functional form. This can help ensure that you have enough observations relative to the number of coefficients.
3. Consider alternative methods: If increasing the number of observations or simplifying the model is not feasible, you may need to reconsider the analysis approach. Depending on your specific situation, alternative methods such as resampling techniques (e.g., bootstrapping) or Bayesian inference may be more appropriate for estimating uncertainty in the coefficients.
