Update resample docs with error propagation details

docs/jwst/resample/main.rst

@@ -34,6 +34,57 @@ WCS of each input image and the WCS of the defined output product.
 This mapping function gets passed to cdriz to drive the actual
 drizzling to create the output product.
 
+
+Error Propagation
+-----------------
+
+The error associated with each resampled pixel can in principle be derived
+from the variance components associated with each input pixel, weighted by
+the square of the input user weights and the square of the overlap between
+the input and output pixels. In practice, the cdriz routine does not currently
+support propagating variance data alongside science images, so the output
+error cannot be precisely calculated.
+
+To approximate the error on a resampled pixel, the variance arrays associated
+with each input image are resampled individually, then combined with a weighted
+sum.  The process is:
+
+#. For each input image, take the square root of each of the read noise variance
+   array to make an error image.
+
+#. Drizzle the read noise error image onto the output WCS, with drizzle
+   parameters matching those used for the science data.
+
+#. Square the resampled read noise to make a variance array.
+
+   a. If the resampling `weight_type` is an inverse variance map (`ivm`), weight
+      the resampled variance by the square of its own inverse.
+
+   #. If the `weight_type` is the exposure time (`exptime`), weight the
+      resampled variance by the square of the exposure time for the image.
+
+#. Add the weighted, resampled read noise variance to a running sum across all
+   images.  Add the weights (unsquared) to a separate running sum across
+   all images.
+
+#. Perform the same steps for the Poisson noise variance and the flat variance.
+   For these components, the weight for the sum is either the resampled read
+   noise variance or else the exposure time.
+
+#. For each variance component (read noise, Poisson, and flat), divide the
+   weighted variance sum by the total weight, squared.
+
+After each variance component is resampled and summed, the final error
+array is computed as the square root of the sum of the three independent
+variance components.  This error image is stored in the ``err`` attribute
+in the output data model or the ``'ERR'`` extension of the FITS file.
+
+It is expected that the output errors computed in this way will
+generally overestimate the true error on the resampled data.  The magnitude
+of the overestimation depends on the details of the pixel weights
+and error images.
+
+
 Context Image
 -------------
 
@@ -93,6 +144,7 @@ context array ``con``, one can do something like this:
 For convenience, this functionality was implemented in the
 :py:func:`~jwst.resample.resample_utils.decode_context` function.
 
+
 Spectroscopic Data
 ------------------