@@ -113,14 +113,14 @@ for μ in [1, 5, 10]:
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113 | 113 | distribution.append(poisson_pmf(y_i, μ)) |
114 | 114 | ax.plot(y_values, |
115 | 115 | distribution, |
116 | | - label=f'$\mu$={μ}', |
| 116 | + label=fr'$\mu$={μ}', |
117 | 117 | alpha=0.5, |
118 | 118 | marker='o', |
119 | 119 | markersize=8) |
120 | 120 | |
121 | 121 | ax.grid() |
122 | 122 | ax.set_xlabel('$y$', fontsize=14) |
123 | | -ax.set_ylabel('$f(y \mid \mu)$', fontsize=14) |
| 123 | +ax.set_ylabel(r'$f(y \mid \mu)$', fontsize=14) |
124 | 124 | ax.axis(xmin=0, ymin=0) |
125 | 125 | ax.legend(fontsize=14) |
126 | 126 | |
@@ -211,14 +211,14 @@ for X in datasets:
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211 | 211 | distribution.append(poisson_pmf(y_i, μ)) |
212 | 212 | ax.plot(y_values, |
213 | 213 | distribution, |
214 | | - label=f'$\mu_i$={μ:.1}', |
| 214 | + label=fr'$\mu_i$={μ:.1}', |
215 | 215 | marker='o', |
216 | 216 | markersize=8, |
217 | 217 | alpha=0.5) |
218 | 218 | |
219 | 219 | ax.grid() |
220 | 220 | ax.legend() |
221 | | -ax.set_xlabel('$y \mid x_i$') |
| 221 | +ax.set_xlabel(r'$y \mid x_i$') |
222 | 222 | ax.set_ylabel(r'$f(y \mid x_i; \beta )$') |
223 | 223 | ax.axis(xmin=0, ymin=0) |
224 | 224 | plt.show() |
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