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| 1 | +<!-- README.md is generated from README.Rmd. Please edit that file--> |
| 2 | +PCSinR |
| 3 | +====== |
| 4 | + |
| 5 | +**The PCSinR package contains all necessary functions for building and simulation Parallel Constraint Satisfaction (PCS) network models within R.** |
| 6 | + |
| 7 | +PCS models are an increasingly used framework throughout psychology: They provide quantitative predictions in a variety of paradigms, ranging from word and letter recognition, for which they were originally developed (McClelland & Rumelhart, 1981; Rumelhart & McClelland, 1982), to complex judgments and decisions (Glöckner & Betsch, 2008; Glöckner, Hilbig, & Jekel, 2014), and many other applications besides. |
| 8 | + |
| 9 | +Installation |
| 10 | +------------ |
| 11 | + |
| 12 | +- The current stable version is available via CRAN, and can be installed by running`install.packages("PCSinR")`. |
| 13 | +- You can install the latest development version directly from GitHub with the`devtools` package. To do so, please run`devtools::install_github("felixhenninger/PCSinR@master")`. |
| 14 | + |
| 15 | +Usage |
| 16 | +----- |
| 17 | + |
| 18 | +The functions in this package simulate a PCS network, given an interconnection matrix. Methods for creating such a matrix from the most common models are forthcoming. |
| 19 | + |
| 20 | +Once a connection matrix has been specified, the model can be simulated easily using the most common parameter set. |
| 21 | + |
| 22 | +```r |
| 23 | +require(PCSinR) |
| 24 | +#> Loading required package: PCSinR |
| 25 | + |
| 26 | +interconnections<-matrix( |
| 27 | + c(0.0000,0.1015,0.0470,0.0126,0.0034,0.0000,0.0000, |
| 28 | +0.1015,0.0000,0.0000,0.0000,0.0000,0.0100,-0.0100, |
| 29 | +0.0470,0.0000,0.0000,0.0000,0.0000,0.0100,-0.0100, |
| 30 | +0.0126,0.0000,0.0000,0.0000,0.0000,0.0100,-0.0100, |
| 31 | +0.0034,0.0000,0.0000,0.0000,0.0000,-0.0100,0.0100, |
| 32 | +0.0000,0.0100,0.0100,0.0100,-0.0100,0.0000,-0.2000, |
| 33 | +0.0000,-0.0100,-0.0100,-0.0100,0.0100,-0.2000,0.0000 ), |
| 34 | +nrow=7 |
| 35 | +) |
| 36 | + |
| 37 | +result<- PCS_run_from_interconnections(interconnections) |
| 38 | +``` |
| 39 | + |
| 40 | +A common simulation result concerns the number of iterations needed until convergence is reached. |
| 41 | + |
| 42 | +```r |
| 43 | +result$convergence |
| 44 | +#> default |
| 45 | +#> 116 |
| 46 | +``` |
| 47 | + |
| 48 | +The output also contains a log of the model states across all iterations. Here, we examine just the final state. |
| 49 | + |
| 50 | +```r |
| 51 | +result$iterations[nrow(result$iterations),] |
| 52 | +#> iteration energy node_1 node_2 node_3 node_4 node_5 node_6 node_7 |
| 53 | +#> 117 116 -0.2916358 1 0.5293124 0.3669084 0.1906411 -0.07023219 0.5477614 -0.5477614 |
| 54 | +``` |
| 55 | + |
| 56 | +General Information |
| 57 | +------------------- |
| 58 | + |
| 59 | +The`PCSinR` package is developed and maintained by Felix Henninger. It is published under the GNU General Public License (version 3 or later). The[NEWS file](NEWS.md) documents the most recent changes. |
| 60 | + |
| 61 | +This work was supported by the University of Mannheim’s Graduate School of Economic and Social Sciences, which is funded by the German Research Foundation. |