Running examples in ‘QCA-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: minimize
> ### Title: Minimize a truth table
> ### Aliases: minimize eqmcc
> ### Keywords: functions
> 
> ### ** Examples
> 
>       
> # -----
> # Lipset binary crisp data
> 
> # the associated truth table
> ttLC <- truthTable(LC, SURV, sort.by = "incl, n", show.cases = TRUE)
> ttLC

  OUT: output value
    n: number of cases in configuration
 incl: sufficiency inclusion score
  PRI: proportional reduction in inconsistency

     DEV URB LIT IND STB   OUT    n  incl  PRI   cases      
32    1   1   1   1   1     1     4  1.000 1.000 BE,CZ,NL,UK
22    1   0   1   0   1     1     2  1.000 1.000 FI,IE      
24    1   0   1   1   1     1     2  1.000 1.000 FR,SE      
 1    0   0   0   0   0     0     3  0.000 0.000 GR,PT,ES   
 2    0   0   0   0   1     0     2  0.000 0.000 IT,RO      
 5    0   0   1   0   0     0     2  0.000 0.000 HU,PL      
 6    0   0   1   0   1     0     1  0.000 0.000 EE         
23    1   0   1   1   0     0     1  0.000 0.000 AU         
31    1   1   1   1   0     0     1  0.000 0.000 DE         

> 
> # conservative solution (Rihoux & De Meur 2009, p.57)
> cLC <- minimize(ttLC)
> cLC

M1: DEV*~URB*LIT*STB + DEV*LIT*IND*STB <-> SURV

> 
> # view the Venn diagram for the associated truth table
> library(venn)
> venn(cLC)
> 
> # add details and case names
> minimize(ttLC, details = TRUE)

M1: DEV*~URB*LIT*STB + DEV*LIT*IND*STB <-> SURV

                     inclS   PRI   covS   covU   cases 
------------------------------------------------------------------- 
1  DEV*~URB*LIT*STB  1.000  1.000  0.500  0.250  FI,IE; FR,SE 
2   DEV*LIT*IND*STB  1.000  1.000  0.750  0.500  FR,SE; BE,CZ,NL,UK 
------------------------------------------------------------------- 
                 M1  1.000  1.000  1.000 

> 
> # negating the outcome
> ttLCn <- truthTable(LC, ~SURV, sort.by = "incl, n", show.cases = TRUE)
> minimize(ttLCn)

M1: ~DEV*~URB*~IND + DEV*LIT*IND*~STB <-> ~SURV

> 
> # parsimonious solution, positive output
> pLC <- minimize(ttLC, include = "?", details = TRUE)
> pLC

M1: DEV*STB <-> SURV

            inclS   PRI   covS   covU   cases 
----------------------------------------------------------------- 
1  DEV*STB  1.000  1.000  1.000    -    FI,IE; FR,SE; BE,CZ,NL,UK 
----------------------------------------------------------------- 
        M1  1.000  1.000  1.000 

> 
> # the associated simplifying assumptions
> pLC$SA
$M1
   DEV URB LIT IND STB
18   1   0   0   0   1
20   1   0   0   1   1
26   1   1   0   0   1
28   1   1   0   1   1
30   1   1   1   0   1

> 
> # parsimonious solution, negative output
> pLCn <- minimize(ttLCn, include = "?", details = TRUE)
> pLCn

M1: ~DEV + ~STB <-> ~SURV

         inclS   PRI   covS   covU   cases 
--------------------------------------------------------------- 
1  ~DEV  1.000  1.000  0.800  0.300  GR,PT,ES; IT,RO; HU,PL; EE 
2  ~STB  1.000  1.000  0.700  0.200  GR,PT,ES; HU,PL; AU; DE 
--------------------------------------------------------------- 
     M1  1.000  1.000  1.000 

> 
> 
> # -----
> # Lipset multi-value crisp data (Cronqvist & Berg-Schlosser 2009, p.80)
> 
> # truth table, conditions all columns from DEV to IND
> # note the sequence operator ":"
> ttLM <- truthTable(LM, SURV, conditions = DEV:IND,
+         sort.by = "incl", show.cases = TRUE)
> 
> # conservative solution, positive output
> minimize(ttLM, details = TRUE)

M1: DEV[2]*LIT[1]*IND[1] + DEV[1]*URB[0]*LIT[1]*IND[0] -> SURV[1]

                                inclS   PRI   covS   covU   cases 
--------------------------------------------------------------------------- 
1         DEV[2]*LIT[1]*IND[1]  1.000  1.000  0.625  0.625  FR,SE; BE,NL,UK 
2  DEV[1]*URB[0]*LIT[1]*IND[0]  1.000  1.000  0.250  0.250  FI,IE 
--------------------------------------------------------------------------- 
                            M1  1.000  1.000  0.875 

> 
> # parsimonious solution, positive output
> minimize(ttLM, include = "?", details = TRUE)

M1: DEV[2] + DEV[1]*IND[0] -> SURV[1]

                  inclS   PRI   covS   covU   cases 
------------------------------------------------------------- 
1         DEV[2]  1.000  1.000  0.625  0.625  FR,SE; BE,NL,UK 
2  DEV[1]*IND[0]  1.000  1.000  0.250  0.250  FI,IE 
------------------------------------------------------------- 
              M1  1.000  1.000  0.875 

> 
> # negate the outcome
> ttLMn <- truthTable(LM, ~SURV, conditions = DEV:IND,
+          sort.by = "incl", show.cases = TRUE)
> 
> # conservative solution, negative output
> minimize(ttLMn, details = TRUE)

M1: DEV[0]*URB[0]*IND[0] + DEV[1]*URB[0]*LIT[1]*IND[1] -> ~SURV[1]

                                inclS   PRI   covS   covU  
---------------------------------------------------------- 
1         DEV[0]*URB[0]*IND[0]  1.000  1.000  0.800  0.800 
2  DEV[1]*URB[0]*LIT[1]*IND[1]  1.000  1.000  0.100  0.100 
---------------------------------------------------------- 
                            M1  1.000  1.000  0.900 

                                cases 
------------------------------------- 
1         DEV[0]*URB[0]*IND[0]  GR,IT,PT,RO,ES; EE,HU,PL
2  DEV[1]*URB[0]*LIT[1]*IND[1]  AU
------------------------------------- 

> 
> # parsimonious solution, positive output
> minimize(ttLMn, include = "?", details = TRUE)

M1: DEV[0] + DEV[1]*URB[0]*IND[1] -> ~SURV[1]

                         inclS   PRI   covS   covU   cases 
----------------------------------------------------------------------------- 
1                DEV[0]  1.000  1.000  0.800  0.800  GR,IT,PT,RO,ES; EE,HU,PL 
2  DEV[1]*URB[0]*IND[1]  1.000  1.000  0.100  0.100  AU 
----------------------------------------------------------------------------- 
                     M1  1.000  1.000  0.900 

> 
> 
> # -----
> # Lipset fuzzy sets data (Ragin 2009, p.112)
> 
> # truth table using a very low inclusion cutoff
> ttLF <- truthTable(LF, SURV, incl.cut = 0.8,
+         sort.by = "incl", show.cases = TRUE)
> 
> # conservative solution
> minimize(ttLF, details = TRUE)

M1: DEV*URB*LIT*IND*STB + DEV*~URB*LIT*~IND*STB -> SURV

                          inclS   PRI   covS   covU   cases 
----------------------------------------------------------------- 
1    DEV*URB*LIT*IND*STB  0.904  0.886  0.454  0.393  BE,CZ,NL,UK 
2  DEV*~URB*LIT*~IND*STB  0.804  0.719  0.265  0.204  FI,IE 
----------------------------------------------------------------- 
                      M1  0.870  0.843  0.658 

> 
> # parsimonious solution
> minimize(ttLF, include = "?", details = TRUE)

M1: DEV*~IND + URB*STB -> SURV

             inclS   PRI   covS   covU   cases 
---------------------------------------------------- 
1  DEV*~IND  0.815  0.721  0.284  0.194  FI,IE 
2   URB*STB  0.874  0.845  0.520  0.430  BE,CZ,NL,UK 
---------------------------------------------------- 
         M1  0.850  0.819  0.714 

> 
> # intermediate solution using directional expectations
> minimize(ttLF, include = "?", details = TRUE,
+          dir.exp = c(DEV, URB, LIT, IND, STB))

From C1P1: 

M1:    DEV*URB*LIT*STB + DEV*LIT*~IND*STB -> SURV 

                     inclS   PRI   covS   covU   cases 
------------------------------------------------------------ 
1   DEV*URB*LIT*STB  0.901  0.879  0.468  0.378  BE,CZ,NL,UK 
2  DEV*LIT*~IND*STB  0.814  0.721  0.282  0.191  FI,IE 
------------------------------------------------------------ 
                 M1  0.866  0.839  0.660 

> 
> # directional expectations can also be specified usin a sequence
> minimize(ttLF, include = "?", details = TRUE, dir.exp = DEV:STB)

From C1P1: 

M1:    DEV*URB*LIT*STB + DEV*LIT*~IND*STB -> SURV 

                     inclS   PRI   covS   covU   cases 
------------------------------------------------------------ 
1   DEV*URB*LIT*STB  0.901  0.879  0.468  0.378  BE,CZ,NL,UK 
2  DEV*LIT*~IND*STB  0.814  0.721  0.282  0.191  FI,IE 
------------------------------------------------------------ 
                 M1  0.866  0.839  0.660 

> 
> 
> # URB as a don't care condition (left unspecified) and
> # experimentally, conjunctural directional expectations
> minimize(ttLF, include = "?", details = TRUE,
+          dir.exp = c(DEV, STB, ~LIT*IND))

From C1P1: 

M1:    DEV*URB*STB + DEV*~IND*STB -> SURV 

                 inclS   PRI   covS   covU   cases 
-------------------------------------------------------- 
1   DEV*URB*STB  0.901  0.879  0.468  0.378  BE,CZ,NL,UK 
2  DEV*~IND*STB  0.814  0.721  0.282  0.191  FI,IE 
-------------------------------------------------------- 
             M1  0.866  0.839  0.660 

> 
> 
> # -----
> # Cebotari & Vink (2013, 2015)
> 
> ttCVF <- truthTable(CVF, outcome = PROTEST, incl.cut = 0.8,
+                     sort.by = "incl, n", show.cases = TRUE)
> 
> pCVF <- minimize(ttCVF, include = "?", details = TRUE)
> pCVF

M1: ~NATPRIDE + DEMOC*GEOCON*POLDIS + (~DEMOC*ETHFRACT*POLDIS +
    DEMOC*ETHFRACT*GEOCON) -> PROTEST 
M2: ~NATPRIDE + DEMOC*GEOCON*POLDIS + (~DEMOC*ETHFRACT*POLDIS +
    DEMOC*ETHFRACT*~POLDIS) -> PROTEST 
M3: ~NATPRIDE + DEMOC*GEOCON*POLDIS + (DEMOC*ETHFRACT*GEOCON +
    ETHFRACT*GEOCON*POLDIS) -> PROTEST 
M4: ~NATPRIDE + DEMOC*GEOCON*POLDIS + (DEMOC*ETHFRACT*~POLDIS +
    ETHFRACT*GEOCON*POLDIS) -> PROTEST 

--------------------------------------------------------------------------------- 
                           inclS   PRI   covS   covU   (M1)   (M2)   (M3)   (M4)  
--------------------------------------------------------------------------------- 
1               ~NATPRIDE  0.899  0.807  0.597  0.121  0.132  0.122  0.136  0.126 
2     DEMOC*GEOCON*POLDIS  0.906  0.805  0.342  0.065  0.065  0.070  0.065  0.065 
--------------------------------------------------------------------------------- 
3  ~DEMOC*ETHFRACT*POLDIS  0.842  0.718  0.299  0.000  0.040  0.040               
4   DEMOC*ETHFRACT*GEOCON  0.935  0.826  0.480  0.000  0.085         0.085        
5  DEMOC*ETHFRACT*~POLDIS  0.932  0.773  0.417  0.000         0.085         0.085 
6  ETHFRACT*GEOCON*POLDIS  0.869  0.786  0.365  0.005                0.045  0.045 
--------------------------------------------------------------------------------- 

                           cases 
-------------------------------- 
3               ~NATPRIDE  CrimRussiansUkr,RussiansUkraine; HungariansYugo,KosovoAlbanians;
                        RussiansLatvia; BasquesSpain; AlbaniansFYROM
4     DEMOC*GEOCON*POLDIS  HungariansRom,CatholicsNIreland; AlbaniansFYROM; RussiansEstonia
-------------------------------- 
3  ~DEMOC*ETHFRACT*POLDIS  HungariansYugo,KosovoAlbanians; GagauzMoldova
4   DEMOC*ETHFRACT*GEOCON  BasquesSpain; SerbsFYROM,CatalansSpain; AlbaniansFYROM; RussiansEstonia
5  DEMOC*ETHFRACT*~POLDIS  BasquesSpain; SerbsFYROM,CatalansSpain
6  ETHFRACT*GEOCON*POLDIS  HungariansYugo,KosovoAlbanians; GagauzMoldova; AlbaniansFYROM;
                        RussiansEstonia
-------------------------------- 

> 
> # inspect the PI chart
> pCVF$PIchart

                         5  15 16 24 27 29 30 31 32
~NATPRIDE                x  x  -  -  x  x  -  x  - 
~DEMOC*ETHFRACT*POLDIS   -  x  x  -  -  -  -  -  - 
DEMOC*ETHFRACT*GEOCON    -  -  -  -  -  x  x  x  x 
DEMOC*ETHFRACT*~POLDIS   -  -  -  -  -  x  x  -  - 
DEMOC*GEOCON*POLDIS      -  -  -  x  -  -  -  x  x 
ETHFRACT*GEOCON*POLDIS   -  x  x  -  -  -  -  x  x 

> 
> # DEMOC*ETHFRACT*~POLDIS is dominated by DEMOC*ETHFRACT*GEOCON
> # using row dominance to solve the PI chart
> pCVFrd <- minimize(ttCVF, include = "?", row.dom = TRUE, details = TRUE)
> 
> # plot the prime implicants on the outcome
> pims <- pCVFrd$pims
> 
> par(mfrow = c(2, 2))
> for(i in 1:4) {
+     XYplot(pims[, i], CVF$PROTEST, cex.axis = 0.6)
+ }
> 
> 
> 
> # -----
> # temporal QCA (Ragin & Strand 2008) serving the input as a dataset,
> # which will automatically be passed to truthTable() as an intermediary
> # step before the minimization
> 
> minimize(RS, outcome = REC, details = TRUE)

Error: The causal condition EBA is not numeric.

Execution halted