diff --git a/ccn2019.rev2.Rmd b/ccn2019.rev2.Rmd
index 16bd274..119fd43 100644
--- a/ccn2019.rev2.Rmd
+++ b/ccn2019.rev2.Rmd
@@ -1,6 +1,8 @@
 ---
 title: "Statistical Properties of the N-Back Sequences"
-output: html_notebook
+output:
+  pdf_document: default
+  html_notebook: default
 ---
 
 # Problems
@@ -19,10 +21,96 @@
 ```{r libraries, message=FALSE, include=FALSE, paged.print=FALSE}
 library(ggplot2)
 library(tidyverse)
-
+library(stringi)
+library(plsRglm)
 ```
 
-```{r datasets}
+```{r params}
 load('./data/CL2015.RData')
+
+window_size <- 8
 ```
 
+
+$P=\{V,D,C,W\}$
+
+$V=\{x_N,x_{T},x_{T,local},x_L,x_{L,local},x_V,x_U,x_S,x_{S,local},x_G\}$
+
+$D=\{\}$
+
+
+
+```{r history}
+
+with_lures <- function(stimulus, stimulus_type, n) {
+  sapply(1:length(stimulus), function(i) {
+    lures <- c(as.character(stimulus[i-n-1]), as.character(stimulus[i-n+1]))
+    are_valid_trials <- i>n && all(!is.na(c(lures,stimulus[i])))
+    ifelse(are_valid_trials && stimulus[i] %in% lures,
+           "lure", 
+           as.character(stimulus_type[i]))
+  })
+}
+
+with_history <- function(stimuli, length=16, fixed=F) {
+  seq <- paste(stimuli, collapse = '')
+  
+  sapply(1:length(stimuli), function(i) {
+    stri_reverse(str_sub(seq, max(1,i-length+1), i))
+  })
+  #ifelse(fixed, h[str_length(h)==size], h)
+}
+
+# $x_{s,local}$
+with_skewness <- function(history) {
+  sapply(history, function(h) {
+    freqs <- table(unlist(str_split(h,"")))
+    sum(sort(freqs, decreasing = T)[1:2]) - 1
+  })
+}
+
+# $x_{u,local}$
+with_lumpiness <- function(history) {
+  sapply(history, function(h) {
+    freqs <- table(unlist(str_split(h,"")))
+    max(freqs) - 1
+  })
+}
+
+
+with_targets_ratio <- function(stimulus_type, length=16) {
+  sapply(1:length(stimulus_type), function(i) {
+    trials <- stimulus_type[max(1,i-length):i]
+    length(trials[trials=="target"]) / length(trials)
+  })
+}
+
+with_lures_ratio <- function(stimulus_type, length=16) {
+  sapply(1:length(stimulus_type), function(i) {
+    trials <- stimulus_type[max(1,i-length):i]
+    length(trials[trials=="lure"]) / length(trials)
+  })
+}
+
+NB2 <- NB %>%
+  group_by(participant, condition, block) %>%
+  mutate(n = ifelse(condition=='2-back',2,3)) %>%
+  mutate(stimulus_type = with_lures(stimulus, stimulus_type, n)) %>%
+  mutate(history = with_history(stimulus, window_size)) %>%
+  mutate(x_sl = with_skewness(history)) %>%
+  mutate(x_ul = with_lumpiness(history)) %>%
+  mutate(x_t = with_targets_ratio(stimulus_type, window_size)) %>%
+  mutate(x_l = with_lures_ratio(stimulus_type, window_size)) %>%
+  ungroup()
+  
+pca <- prcomp(~x_sl+x_ul+x_t+x_l, NB2, center = TRUE,scale. = TRUE, na.action=na.exclude)
+NB2 <- NB2 %>% mutate(pc1=pca$x[,'PC1'], pc2=pca$x[,'PC2'])
+
+rt <- unlist(NB2[,"rt"])
+dm <- NB2[,c("x_sl","x_ul","x_t","x_l")]
+set.seed(250)
+plsR(rt,dm,3)
+
+
+
+```
\ No newline at end of file