4.9 Estimation of Standard Deviation and Coefficient of Variation

This code block computes the standard deviations (sd) and coefficients of variation (cv) for the theta parameters, both observed and predicted. Initially, the summary() function from the rstan package is used to extract the sd values for observed and predicted theta parameters from the Bayesian estimation model (model_bayes). Subsequently, the sd values are organized into matrices ordered by dam2 and given corresponding names. Using these matrices, another matrix is generated containing the coefficients of variation for the observed theta parameters (theta_obs_ordenado_cv). Similarly, ordered matrices are constructed by dam2 for both the sd and cv values of the predicted theta parameters (theta_pred_ordenado_sd and theta_pred_ordenado_cv, respectively).

tasa_obs_ordenado_sd <- matrix(tasa_obs[,"sd"], 
                               nrow = D,
                               ncol = P,byrow = TRUE) 

colnames(tasa_obs_ordenado_sd) <- c("TD_mod_sd", "TO_mod_sd", "TP_mod_sd")
tasa_obs_ordenado_sd%<>% as.data.frame()
tasa_obs_ordenado_sd <- cbind(dam2 = indicador_dam1$dam2,
                              tasa_obs_ordenado_sd)
tasa_obs_ordenado_cv <- tasa_obs_ordenado_sd[,-1]/tasa_obs_ordenado[,-1]

colnames(tasa_obs_ordenado_cv) <- c("TD_mod_cv", "TO_mod_cv", "TP_mod_cv")

tasa_obs_ordenado_cv <- cbind(dam2 = indicador_dam1$dam2,
                              tasa_obs_ordenado_cv)

tasa_pred_ordenado_sd <- matrix(tasa_pred[,"sd"], 
                                nrow = D1,
                                ncol = P,byrow = TRUE)

colnames(tasa_pred_ordenado_sd) <- c("TD_mod_sd", "TO_mod_sd", "TP_mod_sd")
tasa_pred_ordenado_sd%<>% as.data.frame()
tasa_pred_ordenado_sd <- cbind(dam2 = dam_pred$dam2, tasa_pred_ordenado_sd)

tasa_pred_ordenado_cv <- tasa_pred_ordenado_sd[,-1]/tasa_pred_ordenado[,-1]

colnames(tasa_pred_ordenado_cv) <- c("TD_mod_cv", "TO_mod_cv", "TP_mod_cv")

tasa_pred_ordenado_cv <- cbind(dam2 = dam_pred$dam2, tasa_pred_ordenado_cv)

The last step is to consolidate the bases obtained for the point estimate, standard deviation and coefficient of variation.

tasa_obs_ordenado <-
  full_join(tasa_obs_ordenado, tasa_obs_ordenado_sd) %>%
  full_join(tasa_obs_ordenado_cv)

tasa_pred_ordenado <-
  full_join(tasa_pred_ordenado, tasa_pred_ordenado_sd) %>%
  full_join(tasa_pred_ordenado_cv)


estimaciones_obs <- full_join(indicador_dam1,
                              bind_rows(tasa_obs_ordenado, tasa_pred_ordenado))



saveRDS(object = estimaciones_obs, file = "Recursos/05_Empleo/11_estimaciones.rds")
tba(head(estimaciones_obs,10))

dam2	n_upm	n_ocupado	n_desocupado	n_inactivo	Ocupado	Ocupado_se	Ocupado_var	Ocupado_deff	Desocupado	Desocupado_se	Desocupado_var	Desocupado_deff	Inactivo	Inactivo_se	Inactivo_var	Inactivo_deff	TD_mod	TO_mod	TP_mod	TD_mod_sd	TO_mod_sd	TP_mod_sd	TD_mod_cv	TO_mod_cv	TP_mod_cv
0101	17	784	40	487	0.6000	0.0188	0.0004	1.9501	0.0323	0.0079	1e-04	2.6463	0.3677	0.0238	0.0006	3.2225	0.0536	0.5969	0.6307	0.0106	0.0183	0.0183	0.1978	0.0307	0.0290
0201	11	733	40	420	0.6033	0.0213	0.0005	2.2667	0.0450	0.0101	1e-04	2.8606	0.3517	0.0138	0.0002	1.0063	0.0714	0.6030	0.6494	0.0110	0.0166	0.0161	0.1546	0.0276	0.0249
0202	11	617	25	332	0.6448	0.0470	0.0022	9.4431	0.0258	0.0066	0e+00	1.7200	0.3295	0.0448	0.0020	8.8895	0.0553	0.6224	0.6589	0.0196	0.0316	0.0320	0.3552	0.0507	0.0486
0203	12	645	17	363	0.6409	0.0184	0.0003	1.5181	0.0183	0.0070	0e+00	2.7981	0.3408	0.0188	0.0004	1.6228	0.0350	0.6348	0.6579	0.0080	0.0178	0.0176	0.2287	0.0280	0.0267
0204	11	638	69	402	0.5574	0.0258	0.0007	3.0165	0.0583	0.0131	2e-04	3.4711	0.3843	0.0253	0.0006	3.0083	0.0864	0.5695	0.6233	0.0167	0.0225	0.0226	0.1937	0.0395	0.0362
0207	11	473	22	374	0.5350	0.0193	0.0004	1.3071	0.0327	0.0088	1e-04	2.1232	0.4323	0.0176	0.0003	1.0991	0.0578	0.5403	0.5735	0.0109	0.0180	0.0178	0.1886	0.0333	0.0311
0209	8	434	4	307	0.5666	0.0405	0.0016	5.0127	0.0051	0.0028	0e+00	1.1608	0.4284	0.0412	0.0017	5.1834	0.0338	0.5634	0.5832	0.0135	0.0307	0.0317	0.3991	0.0545	0.0543
0211	13	713	11	396	0.6232	0.0314	0.0010	4.7191	0.0103	0.0050	0e+00	2.7466	0.3665	0.0286	0.0008	3.9631	0.0339	0.6096	0.6310	0.0114	0.0251	0.0253	0.3372	0.0412	0.0401
0212	9	639	49	301	0.6179	0.0274	0.0007	3.1548	0.0649	0.0292	9e-04	13.9661	0.3172	0.0235	0.0006	2.5491	0.0935	0.6094	0.6723	0.0175	0.0224	0.0221	0.1870	0.0367	0.0329
0302	10	676	91	327	0.5907	0.0285	0.0008	3.6997	0.0877	0.0148	2e-04	3.0084	0.3215	0.0189	0.0004	1.8052	0.1318	0.5783	0.6662	0.0190	0.0216	0.0209	0.1442	0.0373	0.0313