From 771fd5c7b277d001fffbffcc5634f79ca6cb3af7 Mon Sep 17 00:00:00 2001 From: Pietro Monticone <38562595+pitmonticone@users.noreply.github.com> Date: Fri, 7 Jul 2023 00:02:52 +0200 Subject: [PATCH 1/6] Update arellano.md --- lectures/arellano.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lectures/arellano.md b/lectures/arellano.md index 1da6767f..6f66b1d0 100644 --- a/lectures/arellano.md +++ b/lectures/arellano.md @@ -403,7 +403,7 @@ class Arellano_Economy: self.y_grid = jax.device_put(y_grid) self.P = jax.device_put(P) - # Output recieved while in default, with same shape as y_grid + # Output received while in default, with same shape as y_grid self.def_y = jnp.minimum(def_y_param * jnp.mean(self.y_grid), self.y_grid) def params(self): From f43335d014c5acda9ffe40e15da022a31c347055 Mon Sep 17 00:00:00 2001 From: Pietro Monticone <38562595+pitmonticone@users.noreply.github.com> Date: Fri, 7 Jul 2023 00:02:55 +0200 Subject: [PATCH 2/6] Update ifp_egm.md --- lectures/ifp_egm.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/lectures/ifp_egm.md b/lectures/ifp_egm.md index 4f6a1aaa..cfe9c559 100644 --- a/lectures/ifp_egm.md +++ b/lectures/ifp_egm.md @@ -317,7 +317,7 @@ Notice in the code below that ```{code-cell} ipython3 def K_egm(a_in, σ_in, constants, sizes, arrays): """ - The vectorzied operator K using EGM. + The vectorized operator K using EGM. """ @@ -598,7 +598,7 @@ plt.show() ### Timing -Now let's compare excution time of the two methods +Now let's compare execution time of the two methods ```{code-cell} ipython3 qe.tic() From 59caa7618b0b70cf6d275c1449d97e16b7848866 Mon Sep 17 00:00:00 2001 From: Pietro Monticone <38562595+pitmonticone@users.noreply.github.com> Date: Fri, 7 Jul 2023 00:02:58 +0200 Subject: [PATCH 3/6] Update jax_intro.md --- lectures/jax_intro.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lectures/jax_intro.md b/lectures/jax_intro.md index 2f2fd7b5..5dfca37c 100644 --- a/lectures/jax_intro.md +++ b/lectures/jax_intro.md @@ -515,7 +515,7 @@ Try writing a version of this operation for JAX, using all the same parameters. If you are running your code on a GPU, you should be able to achieve -significantly faster exection. +significantly faster execution. ```{exercise-end} From 03b74a6e26163071dd3771edfca2c50cb212bd5b Mon Sep 17 00:00:00 2001 From: Pietro Monticone <38562595+pitmonticone@users.noreply.github.com> Date: Fri, 7 Jul 2023 00:03:01 +0200 Subject: [PATCH 4/6] Update markov_asset.md --- lectures/markov_asset.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lectures/markov_asset.md b/lectures/markov_asset.md index ae0b24e9..d4225be2 100644 --- a/lectures/markov_asset.md +++ b/lectures/markov_asset.md @@ -205,7 +205,7 @@ $$ $$ Here $\{\epsilon_{c, t}\}$ and $\{\epsilon_{d, t}\}$ are IID and standard -normal, and independent of eachother. +normal, and independent of each other. We can think of $\{X_t\}$ as an aggregate shock that affects both consumption growth and firm profits (and hence dividends). From 68b698d497f6e0b6aeb58eda86bd4e60d20c1c1c Mon Sep 17 00:00:00 2001 From: Pietro Monticone <38562595+pitmonticone@users.noreply.github.com> Date: Fri, 7 Jul 2023 00:03:04 +0200 Subject: [PATCH 5/6] Update mle.md --- lectures/mle.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/lectures/mle.md b/lectures/mle.md index 9d1c69d0..1432e6c8 100644 --- a/lectures/mle.md +++ b/lectures/mle.md @@ -347,7 +347,7 @@ $$ \beta_2 = 0.5 $$ -Try to obtain the approximate values of $\beta_0,\beta_1,\beta_2$, by simulating a Poission Regression Model such that +Try to obtain the approximate values of $\beta_0,\beta_1,\beta_2$, by simulating a Poisson Regression Model such that $$ y_t \sim {\rm Poisson}(\lambda_t) @@ -391,7 +391,7 @@ We compute $\lambda$ using {eq}`lambda_mle` λ = jnp.exp(β_0 + β_1 * x + β_2 * x**2) ``` -Let's define $y_t$ by sampling from a Poission distribution with mean as $\lambda_t$. +Let's define $y_t$ by sampling from a Poisson distribution with mean as $\lambda_t$. ```{code-cell} ipython3 y = jax.random.poisson(key, λ, shape) From adee78207eef0d1f6f5346af1a87831400b80f34 Mon Sep 17 00:00:00 2001 From: Pietro Monticone <38562595+pitmonticone@users.noreply.github.com> Date: Fri, 7 Jul 2023 00:03:06 +0200 Subject: [PATCH 6/6] Update newtons_method.md --- lectures/newtons_method.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/lectures/newtons_method.md b/lectures/newtons_method.md index 01051c25..10d7e49f 100644 --- a/lectures/newtons_method.md +++ b/lectures/newtons_method.md @@ -105,7 +105,7 @@ for this particular question. ### A High-Dimensional Version -Let's now shift to a linear algebra formulation, which alllows us to handle +Let's now shift to a linear algebra formulation, which allows us to handle arbitrarily many goods. The supply function remains unchanged, @@ -325,7 +325,7 @@ initLs = [jnp.ones(3), ``` -Then define the multivariate version of the formula for the [law of motion of captial](https://python.quantecon.org/newton_method.html#solow) +Then define the multivariate version of the formula for the [law of motion of capital](https://python.quantecon.org/newton_method.html#solow) ```{code-cell} ipython3 def multivariate_solow(k, A=A, s=s, α=α, δ=δ):