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Fix math rendering in docstrings #315
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I have added this branch to |
Thanks!
… On 4 Jul 2017, at 4:13 pm, mmcky ***@***.***> wrote:
I have added this branch to rtd for review -- it is currently building.
https://readthedocs.org/projects/quanteconpy/builds/5642386/
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@natashawatkins this is really nice work! I had a few comments for you from my brief review. rtd
is also setup for review of this branch now.
@@ -210,15 +234,15 @@ def update(self, y): | |||
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def stationary_values(self): | |||
""" | |||
Computes the limit of Sigma_t as t goes to infinity by | |||
solving the associated Riccati equation. Computation is via the | |||
Computes the limit of :math:`\Sigma_t` as t goes to infinity by |
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should t
be inline math?
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I'm not sure about this - it could be? But maybe unnecessary?
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Returns | ||
------- | ||
P : array_like(float) | ||
P is part of the value function representation of | ||
V(x) = xPx + d | ||
:math:`V(x) = x'Px + d` |
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good catch with x'
quantecon/lss.py
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given :math:`x_0` = x0 | ||
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Here :math:`x_t` and :math:`v_t` are both n x 1 and A is n x n. |
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should A
be inline math?
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Fixed thanks
y_t = \bar{y} + \rho y_{t-1} + \varepsilon_t | ||
where \varepsilon_t is i.i.d. normal of mean 0, std dev of sigma | ||
:math:`y_t = \bar{y} + \rho y_{t-1} + \varepsilon_t` | ||
where :math:`\varepsilon_t` is i.i.d. normal of mean 0, std dev of sigma |
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what is the difference between \varepsilon
and \epsilon
?
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Apparently they look slightly different but represent the same symbol - https://tex.stackexchange.com/questions/304534/what-does-the-var-prefix-stand-for-in-varphi-and-varepsilon-etc
quantecon/markov/approximation.py
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using Tauchen's method. Here {u_t} is an iid Gaussian process with zero | ||
mean. | ||
using Tauchen's method. Here :math:`{u_t}`` is an iid Gaussian process |
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should this have two end ticks?
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Fixed thanks
quantecon/matrix_eqn.py
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X = A'XA - (N + B'XA)'(B'XB + R)^{-1}(N + B'XA) + Q | ||
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via a modified structured doubling algorithm. An explanation of the | ||
algorithm can be found in the reference below. | ||
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Note that SciPy also has a discrete riccati equation solver. However it | ||
cannot handle the case where R is not invertible, or when N is nonzero. | ||
Both of these cases can be handled in the algorithm implemented below. | ||
cannot handle the case where :math:`R` is not invertible, or when N is |
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should N
be inline math?
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Fixed thanks
@natashawatkins Thanks! Great work. I have checked all details but it's a big step forward even if some errors remain. @mmcky Is the maintainer of the package so I'll leave the merge up to him. |
Thanks @natashawatkins. |
Here :math:`x` is n x 1, :math:`u` is k x 1, :math:`w` is j x 1 and the | ||
matrices are conformable for these dimensions. The sequence :math:`{w_t}` | ||
is assumed to be white noise, with zero mean and | ||
:math:`\mathbb{E} [ w_t' w_t ] = I`, the j x j identity. |
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@mmcky I think w_t w_t
is also not conformable? Could you check please? Thanks
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Sorry I forgot to click submit review
Sorry about such a large commit (did not expect to fix this much)
A lot of math renderings weren't working either due to:
Also
Best way to review is probably to
make html
in quantecon/docs