Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

. 2013 Mar 14;9(3):e1002922. doi: 10.1371/journal.pcbi.1002922

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

© 2013 Granot-Atedgi et al

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.

PMC Copyright notice

. The results for the S2 model are shown in (a), the results for the S1 model in (b), and the results for a full conditionally independent model (T1) in (c). The first row displays the log ratio of model to empirical probabilities for various codewords (dots), as a function of that codeword's empirical frequency in the recorded data. The model probabilities were estimated by generating Monte Carlo samples drawn from the corresponding model distributions; only patterns that were generated in the MC run as well as found in the recorded data are shown. GoF quantifies the deviation between true and predicted of the non-silent codewords shown in the plot; smaller values indicate better agreement (see Methods). The second row summarizes this scatterplot by binning codewords according to their frequency, and showing the average log probability ratio in the bin (solid line), as well as the std scatter across the codewords in the bin (shaded area). The highly probable all-silent state, , is shown separately as a circle. The third row shows the overlap between 500 most frequent patterns in the data and 500 most likely patterns generated by the model (see text). Models were fit on training repeats; comparisons are done only with test repeats data.

Inline graphic — . The results for the S2 model are shown in (a), the results for the S1 model in (b), and the results for a full conditionally independent model (T1) in (c). The first row displays the log ratio of model to empirical probabilities for various codewords (dots), as a function of that codeword's empirical frequency in the recorded data. The model probabilities were estimated by generating Monte Carlo samples drawn from the corresponding model distributions; only patterns that were generated in the MC run as well as found in the recorded data are shown. GoF quantifies the deviation between true and predicted of the non-silent codewords shown in the plot; smaller values indicate better agreement (see Methods). The second row summarizes this scatterplot by binning codewords according to their frequency, and showing the average log probability ratio in the bin (solid line), as well as the std scatter across the codewords in the bin (shaded area). The highly probable all-silent state, , is shown separately as a circle. The third row shows the overlap between 500 most frequent patterns in the data and 500 most likely patterns generated by the model (see text). Models were fit on training repeats; comparisons are done only with test repeats data.