remove model 5 from test code, for now

example-notebooks/Test new_gamma_survival_model with simulated data.ipynb

@@ -833,90 +833,6 @@
     "survivalstan.utils.print_stan_summary([testfit4], pars=['lp__', 'alpha', 'beta'])"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## model 5: move idx_cens & idx_obs into transformed-data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "model_code5 = '''\n",
-    "functions {\n",
-    "    int count_value(vector a, real val) {\n",
-    "        int s;\n",
-    "        s = 0;\n",
-    "        for (i in 1:num_elements(a)) \n",
-    "            if (a[i] == val) \n",
-    "                s = s + 1;\n",
-    "        return s;\n",
-    "    }\n",
-    "\n",
-    "  // Defines the log survival\n",
-    "  real surv_gamma_lpdf (vector t, vector d, real shape, vector rate, int num_cens, int num_obs) {\n",
-    "    vector[2] log_lik;\n",
-    "    int idx_obs[num_obs];\n",
-    "    int idx_cens[num_cens];\n",
-    "    real prob;\n",
-    "    int i_cens;\n",
-    "    int i_obs;\n",
-    "    i_cens = 1;\n",
-    "    i_obs = 1;\n",
-    "    for (i in 1:num_elements(t)) {\n",
-    "        if (d[i] == 1) {\n",
-    "            idx_obs[i_obs] = i;\n",
-    "            i_obs = i_obs+1;\n",
-    "        }\n",
-    "        else {\n",
-    "            idx_cens[i_cens] = i;\n",
-    "            i_cens = i_cens+1;\n",
-    "        }\n",
-    "    }\n",
-    "    print(idx_obs);\n",
-    "    log_lik[1] = gamma_lpdf(t[idx_obs] | shape, rate[idx_obs]);\n",
-    "    log_lik[2] = gamma_lccdf(t[idx_cens] | shape, rate[idx_cens]);\n",
-    "    prob = sum(log_lik);\n",
-    "    return prob;\n",
-    "  }\n",
-    "}\n",
-    "data {\n",
-    "  int N;                            // number of observations\n",
-    "  vector<lower=0>[N] y;             // observed times\n",
-    "  vector<lower=0,upper=1>[N] event; // censoring indicator (1=observed, 0=censored)\n",
-    "  int M;                            // number of covariates\n",
-    "  matrix[N, M] x;                   // matrix of covariates (with n rows and H columns)\n",
-    "}\n",
-    "transformed data {\n",
-    "  int num_cens;\n",
-    "  int num_obs;\n",
-    "  num_obs = count_value(event, 1);\n",
-    "  num_cens = N - num_obs;\n",
-    "}\n",
-    "parameters {\n",
-    "  vector[M] beta;         // Coefficients in the linear predictor (including intercept)\n",
-    "  real<lower=0> alpha;    // shape parameter\n",
-    "}\n",
-    "transformed parameters {\n",
-    "  vector[N] linpred;\n",
-    "  vector[N] mu;\n",
-    "  linpred = x*beta;\n",
-    "  mu = exp(linpred);\n",
-    "}\n",
-    "model {\n",
-    "  alpha ~ gamma(0.01,0.01);\n",
-    "  beta ~ normal(0,5);\n",
-    "  y ~ surv_gamma(event, alpha, mu, num_cens, num_obs);\n",
-    "}\n",
-    "'''"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},