Add link to arxiv preprint

README.Rmd

@@ -38,7 +38,7 @@ distribution and the approximated one.
 The method is fully described in the paper:
 
 > García, C.A., Otero, A., Félix, P., Presedo, J. & Márquez D.G., (2017). **Non-parametric Estimation of Stochastic Differential Equations with 
-Sparse Gaussian Processes** _(under review)_.
+Sparse Gaussian Processes** _(under review)_,  [preprint](https://arxiv.org/abs/1704.04375).
 
 ## Installation
 `voila` is not currently available on [CRAN](http://cran.r-project.org/), but it

README.md

@@ -12,7 +12,7 @@ where W represents a [Wiener process](https://en.wikipedia.org/wiki/Wiener_proce
 
 The method is fully described in the paper:
 
-> García, C.A., Otero, A., Félix, P., Presedo, J. & Márquez D.G., (2017). **Non-parametric Estimation of Stochastic Differential Equations with Sparse Gaussian Processes** *(under review)*.
+> García, C.A., Otero, A., Félix, P., Presedo, J. & Márquez D.G., (2017). **Non-parametric Estimation of Stochastic Differential Equations with Sparse Gaussian Processes** *(under review)*, [preprint](https://arxiv.org/abs/1704.04375).
 
 Installation
 ------------
@@ -32,6 +32,28 @@ from a single realization of an unidimensional [Ornstein–Uhlenbeck](https://en
 
 ``` r
 library("voila", quietly = TRUE, verbose = FALSE)
+#> 
+#> Attaching package: 'zoo'
+#> The following objects are masked from 'package:base':
+#> 
+#>     as.Date, as.Date.numeric
+#> 
+#> Attaching package: 'expm'
+#> The following object is masked from 'package:Matrix':
+#> 
+#>     expm
+#> ############################################
+#> This is YUIMA Project package.
+#> Check for the latest development version at:
+#> http://R-Forge.R-Project.org/projects/yuima
+#> ############################################
+#> 
+#> Attaching package: 'yuima'
+#> The following object is masked from 'package:stats':
+#> 
+#>     simulate
+#> Warning: replacing previous import by 'Rcpp::loadModule' when loading
+#> 'voila'
 # simulate a Ornstein-Uhlenbeck time series using voila ---------------------
 set.seed(1234)
 samplingPeriod = 0.001
@@ -90,21 +112,18 @@ diffKer =  sde_kernel("exp_const_kernel",
 inference = sde_vi(targetIndex, x, samplingPeriod, pseudoInputs, 
                    driftKer, diffKer, diffParams$v)
 #> Starting Variational Inference
-#> Iteration 1| Distributions update | L = 36689.451
-#> Iteration 1| Hyperparameter optimization | L = 36689.964
-#> HP = 0.995 1.49 0.00205 1.5 -2.14 -1.65 -1.18 -0.7 -0.236 0.26 0.717 1.19 1.69 2.16 -0.851 
-#> 
-#> Iteration 2| Distributions update | L = 36697.556
-#> Iteration 2| Hyperparameter optimization | L = 36697.586
-#> HP = 0.998 1.51 0.00196 1.51 -2.14 -1.65 -1.18 -0.7 -0.236 0.26 0.716 1.19 1.69 2.16 -0.841 
+#> Initial Lower Bound L = -59074
+#> Iteration 1| Distributions update | L = 36689.822
+#> Iteration 1| Hyperparameter optimization | L = 36690.319
+#> HP = 0.996 1.49 0.00182 1.5 -2.14 -1.65 -1.18 -0.7 -0.235 0.259 0.718 1.19 1.69 2.16 -0.824 
 #> 
-#> Iteration 3| Distributions update | L = 36697.601
-#> Iteration 3| Hyperparameter optimization | L = 36697.624
-#> HP = 1 1.53 0.0019 1.52 -2.14 -1.65 -1.18 -0.7 -0.235 0.261 0.716 1.19 1.69 2.16 -0.83 
+#> Iteration 2| Distributions update | L = 36697.619
+#> Iteration 2| Hyperparameter optimization | L = 36697.639
+#> HP = 0.998 1.51 0.00178 1.51 -2.14 -1.65 -1.18 -0.7 -0.235 0.259 0.718 1.19 1.69 2.16 -0.813 
 #> 
-#> Iteration 4| Distributions update | L = 36697.639
-#> Iteration 4| Hyperparameter optimization | L = 36697.659
-#> HP = 1 1.55 0.00185 1.53 -2.14 -1.65 -1.18 -0.7 -0.235 0.261 0.716 1.19 1.69 2.16 -0.818 
+#> Iteration 3| Distributions update | L = 36697.654
+#> Iteration 3| Hyperparameter optimization | L = 36697.654
+#> HP = 0.998 1.51 0.00178 1.51 -2.14 -1.65 -1.18 -0.7 -0.235 0.259 0.718 1.19 1.69 2.16 -0.813 
 #> 
 #> CONVERGENCE
 # Analyze results  --------------------------------------------------------

vignettes/do_events.Rmd

@@ -114,5 +114,5 @@ function may be found at reference [1].
 This example is discussed in detail in the paper:
 
 > [1] García, C.A., Otero, A., Félix, P., Presedo, J. & Márquez D.G., (2017). **Non-parametric Estimation of Stochastic Differential Equations with 
-Sparse Gaussian Processes** _(under review)_.
+Sparse Gaussian Processes** _(under review)_,  [preprint](https://arxiv.org/abs/1704.04375).