Update app.py

app.py

@@ -50,37 +50,37 @@ st.write(f"### Y = \u03B1 + \u03B2X + \u03C3")
 alpha_prior_option = st.selectbox("Choose an option for alpha prior:", ["Normal", "Laplace", "Cauchy"])
 if alpha_prior_option == "Normal":
     alpha_loc = st.slider("Select a mean value for alpha", -10.0, 10.0, 0.0, 0.1)
-    alpha_scale = st.slider("Select a standard deviation value for alpha", 0.0, 10.0, 1.0, 0.1)
+    alpha_scale = st.slider("Select a standard deviation value for alpha", 0.01, 10.0, 1.0, 0.1)
     alpha_prior = dist.Normal(alpha_loc, alpha_scale)
 elif alpha_prior_option == "Laplace":
     alpha_loc = st.slider("Select a mean value for alpha", -10.0, 10.0, 0.0, 0.1)
-    alpha_scale = st.slider("Select a scale value for alpha", 0.0, 10.0, 1.0, 0.1)
+    alpha_scale = st.slider("Select a scale value for alpha", 0.01, 10.0, 1.0, 0.1)
     alpha_prior = dist.Laplace(alpha_loc, alpha_scale)
 elif alpha_prior_option == "Cauchy":
     alpha_loc = st.slider("Select a location value for alpha", -10.0, 10.0, 0.0, 0.1)
-    alpha_scale = st.slider("Select a scale value for alpha", 0.0, 10.0, 1.0, 0.1)
+    alpha_scale = st.slider("Select a scale value for alpha", 0.01, 10.0, 1.0, 0.1)
     alpha_prior = dist.Cauchy(alpha_loc, alpha_scale)
 
 beta_prior_option = st.selectbox("Choose an option for beta prior:", ["Normal", "Laplace", "Cauchy"])
 if beta_prior_option == "Normal":
     beta_loc = st.slider("Select a mean value for beta", -10.0, 10.0, 0.0, 0.1)
-    beta_scale = st.slider("Select a standard deviation value for beta", 0.0, 10.0, 1.0, 0.1)
+    beta_scale = st.slider("Select a standard deviation value for beta", 0.01, 10.0, 1.0, 0.1)
     beta_prior = dist.Normal(beta_loc, beta_scale)
 elif beta_prior_option == "Laplace":
     beta_loc = st.slider("Select a mean value for beta", -10.0, 10.0, 0.0, 0.1)
-    beta_scale = st.slider("Select a scale value for beta", 0.0, 10.0, 1.0, 0.1)
+    beta_scale = st.slider("Select a scale value for beta", 0.01, 10.0, 1.0, 0.1)
     beta_prior = dist.Laplace(beta_loc, beta_scale)
 elif beta_prior_option == "Cauchy":
     beta_loc = st.slider("Select a location value for beta", -10.0, 10.0, 0.0, 0.1)
-    beta_scale = st.slider("Select a scale value for beta", 0.0, 10.0, 1.0, 0.1)
+    beta_scale = st.slider("Select a scale value for beta", 0.01, 10.0, 1.0, 0.1)
     beta_prior = dist.Cauchy(beta_loc, beta_scale)
 
 sigma_prior_option = st.selectbox("Choose an option for sigma prior:", ["HalfNormal", "HalfCauchy"])
 if sigma_prior_option == "HalfNormal":
-    sigma_scale = st.slider("Select a scale value for sigma", 0.0, 10.0, 1.0, 0.1)
+    sigma_scale = st.slider("Select a scale value for sigma", 0.01, 10.0, 1.0, 0.1)
     sigma_prior = dist.HalfNormal(sigma_scale)
 elif sigma_prior_option == "HalfCauchy":
-    sigma_scale = st.slider("Select a scale value for sigma", 0.0, 10.0, 1.0, 0.1)
+    sigma_scale = st.slider("Select a scale value for sigma", 0.01, 10.0, 1.0, 0.1)
     sigma_prior = dist.HalfCauchy(sigma_scale)
 
 rng_key = random.PRNGKey(0)