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| author | Thibaut Horel <thibaut.horel@gmail.com> | 2015-02-06 01:58:36 -0500 |
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| committer | Thibaut Horel <thibaut.horel@gmail.com> | 2015-02-06 01:58:36 -0500 |
| commit | b07ea233bc2c519404f44f24c03b9a2c2f94c290 (patch) | |
| tree | ecb6ba126c1714cdd20485be10518d6dad6e67f5 /paper | |
| parent | 0b26569f6ec37266b449c01d9049118dc022dbfc (diff) | |
| download | cascades-b07ea233bc2c519404f44f24c03b9a2c2f94c290.tar.gz | |
Fix more bug
Diffstat (limited to 'paper')
| -rw-r--r-- | paper/sections/model.tex | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/paper/sections/model.tex b/paper/sections/model.tex index cf69960..36829f2 100644 --- a/paper/sections/model.tex +++ b/paper/sections/model.tex @@ -61,7 +61,7 @@ where $f: \reals \rightarrow [0,1]$ \end{definition} In other words, each generalized linear cascade provides, for each node $j \in -V$ a series of measurements $(X^t, X^t_j)_{t \in {\cal T}_j}}$ sampled from +V$ a series of measurements $(X^t, X^{t+1}_j)_{t \in {\cal T}_j}$ sampled from a generalized linear model. Note also that $\E[X^{t+1}_i\,|\,X^t] = f(\inprod{\theta_i}{X^t})$. As such, $f$ can be interpreted as the inverse link function of our generalized linear cascade model. |
