diff --git a/R/animation_functions.r b/R/animation_functions.r
index 44c7008..7bd02a6 100644
--- a/R/animation_functions.r
+++ b/R/animation_functions.r
@@ -253,7 +253,7 @@ dagfx_anim_forward <- function( the_dag , Y , X , n_frames , n_loops=3 , path_fr
     print(dat)
 
     # organize colors
-    if ( class(color_list)=="list" ) {
+    if ( is.list(color_list) ) {
         # named list, so sort in order of uvars
         color_list <- unlist(color_list)[uvars]
     }
diff --git a/R/compare.r b/R/compare.r
index dfba2a5..b90457c 100644
--- a/R/compare.r
+++ b/R/compare.r
@@ -29,7 +29,7 @@ compare <- function( ... , n=1e3 , sort="WAIC" , func=WAIC , WAIC=TRUE , refresh
 
     # use substitute to deparse the func argument
     the_func <- func
-    if ( class(the_func) != "character" )
+    if ( !is.character(the_func) )
         the_func <- deparse(substitute(func))
     
     # check class of fit models and warn when more than one class represented
@@ -229,7 +229,7 @@ compare_old <- function( ... , nobs=NULL , sort="AICc" , BIC=FALSE , DIC=FALSE ,
         pD.list <- rep( NA , length(L) )
         for ( i in 1:length(L) ) {
             m <- L[[i]]
-            if ( class(m)=="map" ) {
+            if ( inherits(m, "map") ) {
                 post <- sample.qa.posterior( m , n=DICsamples )
                 message( paste("Computing DIC for model",mnames[i]) )
                 dev <- sapply( 1:nrow(post) , 
diff --git a/R/distributions.r b/R/distributions.r
index 0a9eacb..b513e3e 100644
--- a/R/distributions.r
+++ b/R/distributions.r
@@ -350,7 +350,7 @@ dgnorm <- function( x , mu , alpha , beta , log=FALSE ) {
 # categorical distribution for multinomial models
 
 dcategorical <- function( x , prob , log=TRUE ) {
-    if ( class(prob)=="matrix" ) {
+    if ( is.matrix(prob) ) {
         # vectorized probability matrix
         # length of x needs to match nrow(prob)
         logp <- sapply( 1:nrow(prob) , function(i) log(prob[i,x[i]]) )
diff --git a/R/drawdag.R b/R/drawdag.R
index cf2b999..2a966b8 100644
--- a/R/drawdag.R
+++ b/R/drawdag.R
@@ -4,7 +4,7 @@ drawdag <- function( x , col_arrow="black" , col_segment="black" , col_labels="b
     require(dagitty)
 
     # check for list of DAGs
-    if ( class(x)=="list" ) {
+    if ( is.list(x) ) {
         n <- length(x)
         y <- make.grid(n)
         par(mfrow=y)
diff --git a/R/drawdag_igraph.R b/R/drawdag_igraph.R
index b3f2622..41777c5 100644
--- a/R/drawdag_igraph.R
+++ b/R/drawdag_igraph.R
@@ -40,7 +40,7 @@ graphdag <- function( x ,
         for ( uv in unobs_vars ) the_shapes[ which(the_vars==uv) ] <- "circle"
     }
     if ( interact==FALSE ) {
-        if ( class(layout)!="matrix" )
+        if ( !is.matrix(layout) )
             the_layout <- do.call( layout , list(mgraph) )
         else
             the_layout <- layout
diff --git a/R/ensemble.R b/R/ensemble.R
index d16f416..51c35f0 100644
--- a/R/ensemble.R
+++ b/R/ensemble.R
@@ -11,7 +11,7 @@ ensemble <- function( ... , data , n=1e3 , func=WAIC , weights , refresh=0 , rep
     if ( missing(weights) ) {
         if ( length(L)>1 ) {
             use_func <- func
-            if ( class(use_func) != "character" )
+            if ( !is.character(use_func) )
                 use_func <- deparse(substitute(func))
             ictab <- compare( ... , func=use_func , refresh=refresh , n=n , sort=FALSE )
             rownames(ictab) <- mnames
diff --git a/R/glimmer.R b/R/glimmer.R
index cc54092..2d67634 100644
--- a/R/glimmer.R
+++ b/R/glimmer.R
@@ -50,7 +50,7 @@ xparse_glimmer_formula <- function( formula , data ) {
     # find fixed effects list by deleting random effects and expanding
     f_nobars <- nobars( formula )
     # catch implied intercept error -- happens when right side of formula is only () blocks
-    if ( class(f_nobars)=="name" & length(f_nobars)==1 ) {
+    if ( is.name(f_nobars) & length(f_nobars)==1 ) {
         f_nobars <- nobars( as.formula( paste( deparse(formula) , "+ 1" ) ) )
     }
     #fixef <- make.names( colnames( model.matrix( f_nobars , data ) ) )
@@ -62,7 +62,7 @@ xparse_glimmer_formula <- function( formula , data ) {
     # mdat <- cbind( data[[outcome_name]] , mdat )
     # colnames(mdat)[1] <- outcome_name
     outcome <- model.frame( f_nobars , data )[,1]
-    if ( class(outcome)=="matrix" ) {
+    if ( is.matrix(outcome) ) {
         # fix outcome name
         outcome_name <- colnames( outcome )[1]
     }
@@ -81,7 +81,7 @@ xparse_glimmer_formula <- function( formula , data ) {
             if ( FALSE ) { # check index variables?
                 if ( TRUE ) {
                     # check that grouping vars are class integer
-                    if ( class( data[[name]] )!="integer" ) {
+                    if ( !is.integer( data[[name]] ) ) {
                         stop( paste( "Grouping variables must be integer type. '" , name , "' is instead of type: " , class( data[[name]] ) , "." , sep="" ) )
                     }
                     # check that values are contiguous
@@ -102,7 +102,7 @@ xparse_glimmer_formula <- function( formula , data ) {
             
             # parse formula
             v <- var[[i]][[2]]
-            if ( class(v)=="numeric" ) {
+            if ( is.numeric(v) ) {
                 # just intercept
                 ranef[[ name ]] <- "(Intercept)"
             } else {
@@ -131,7 +131,7 @@ glimmer <- function( formula , data , family=gaussian , prefix=c("b_","v_") , de
     
     # convert family to text
     family.orig <- family
-    if ( class(family)=="function" ) {
+    if ( is.function(family) ) {
         family <- do.call(family,args=list())
     }
     link <- family$link
@@ -155,7 +155,7 @@ glimmer <- function( formula , data , family=gaussian , prefix=c("b_","v_") , de
     )
     
     # check input
-    if ( class(formula)!="formula" ) stop( "Input must be a glmer-style formula." )
+    if ( !inherits(formula, "formula") ) stop( "Input must be a glmer-style formula." )
     if ( missing(data) ) stop( "Need data" )
     
     f <- formula
@@ -170,7 +170,7 @@ glimmer <- function( formula , data , family=gaussian , prefix=c("b_","v_") , de
     # check for size variable in Binomial
     dtext <- family_liks[[family]]
     if ( family=="binomial" ) {
-        if ( class(pf$y)=="matrix" ) {
+        if ( is.matrix(pf$y) ) {
             # cbind input
             pf$dat[[pf$yname]] <- pf$y[,1]
             pf$dat[[concat(pf$yname,"_size")]] <- apply(pf$y,1,sum)
diff --git a/R/map-quap.r b/R/map-quap.r
index 2df982f..e70c38f 100644
--- a/R/map-quap.r
+++ b/R/map-quap.r
@@ -28,8 +28,8 @@ quap <- function( flist , data , start , method="BFGS" , hessian=TRUE , debug=FA
     ########################################
     # check arguments
     if ( missing(flist) ) stop( "Formula required." )
-    if ( class(flist) != "list" ) {
-        if ( class(flist)=="formula" ) {
+    if ( !is.list(flist) ) {
+        if ( inherits(flist, "formula") ) {
             flist <- list(flist)
         } else {
             stop( "Formula or list of formulas required." )
@@ -137,7 +137,7 @@ quap <- function( flist , data , start , method="BFGS" , hessian=TRUE , debug=FA
         LHS <- f[[2]]
         flag_monad_linear_model <- FALSE
         if ( length(RHS)==1 ) {
-            if ( class(RHS)=="numeric" | class(RHS)=="name" )
+            if ( is.numeric(RHS) || is.name(RHS) )
                 flag_monad_linear_model <- TRUE
             fname <- ""
         } else {
@@ -152,7 +152,7 @@ quap <- function( flist , data , start , method="BFGS" , hessian=TRUE , debug=FA
             n_args <- length(RHS)
             args_list <- as.list(RHS)
             # check for LHS with brackets []
-            if ( class(LHS)=="call" ) {
+            if ( is.call(LHS) ) {
                 if ( as.character(LHS[[1]])=="[" ) {
                     ival <- suppressWarnings( as.numeric(as.character(LHS[[3]])) )
                     if ( is.na(ival) ) {
@@ -222,10 +222,10 @@ quap <- function( flist , data , start , method="BFGS" , hessian=TRUE , debug=FA
     if ( length(flist) > 1 ) {
         flag_flatten <- FALSE
         for ( i in 2:length(flist) ) {
-            if ( !(class(flist[[i]])=="formula") )
+            if ( !inherits(flist[[i]], "formula") )
                 stop( "Input not a formula." )
             LHS <- flist[[i]][[2]]
-            if ( class(LHS)=="call" ) {
+            if ( is.call(LHS) ) {
                 fname <- as.character(LHS[[1]])
                 if ( fname=="c" | fname=="[" | fname %in% link.names ) {
                     if ( fname=="c" ) {
@@ -279,7 +279,7 @@ quap <- function( flist , data , start , method="BFGS" , hessian=TRUE , debug=FA
         # loop in reverse order, so linear models lower down get pulled up
         for ( i in length(flist2):2 ) {
             # linear models are class list
-            if ( class(flist2[[i]])=="list" ) {
+            if ( is.list(flist2[[i]]) ) {
                 LHS <- flist2[[i]][[1]]
                 RHS <- flist2[[i]][[2]]
                 # save current likelihood, so can check for link
@@ -297,7 +297,7 @@ quap <- function( flist , data , start , method="BFGS" , hessian=TRUE , debug=FA
                 if ( i > 2 ) {
                     # RHSp <- paste( "(" , RHS , ")" , collapse="" )
                     for ( j in (i-1):2 ) {
-                        if ( class(flist2[[j]])=="list" ) {
+                        if ( is.list(flist2[[j]]) ) {
                             #flist2[[j]][[2]] <- gsub( LHS , RHSp , flist2[[j]][[2]] )
                             flist2[[j]][[2]] <- mygrep( LHS , RHS , flist2[[j]][[2]] , add.par=TRUE )
                         } else {
@@ -314,7 +314,7 @@ quap <- function( flist , data , start , method="BFGS" , hessian=TRUE , debug=FA
         flist3 <- list()
         j <- 1
         for ( i in 1:length(flist2) ) {
-            if ( class(flist2[[i]]) != "list" ) {
+            if ( !is.list(flist2[[i]]) ) {
                 flist3[[j]] <- flist2[[i]]
                 j <- j + 1
             }
@@ -352,7 +352,7 @@ quap <- function( flist , data , start , method="BFGS" , hessian=TRUE , debug=FA
             # scan formula for right prior
             for ( g in 2:length(flist) ) {
                 # check for `[`
-                if ( class(flist[[g]][[2]])=="call" ) {
+                if ( is.call(flist[[g]][[2]]) ) {
                     # assume `[`, because other calls should be purged by now
                     the_par_with_index <- deparse(flist[[g]][[2]])
                     the_par <- as.character( flist[[g]][[2]][[2]] )
@@ -368,7 +368,7 @@ quap <- function( flist , data , start , method="BFGS" , hessian=TRUE , debug=FA
                                 # get length of vector by scanning priors
                                 max_index <- 1
                                 for ( h in 2:length(flist) ) {
-                                    if ( class(flist[[h]][[2]])=="call" ) {
+                                    if ( is.call(flist[[h]][[2]]) ) {
                                         if ( as.character(flist[[h]][[2]][[2]])=="[" & as.character(flist[[h]][[2]][[3]])==the_par ) {
                                             nval <- suppressWarnings( as.numeric(flist[[h]][[2]][[3]]) )
                                             if ( !is.null(nval) ) {
@@ -463,7 +463,7 @@ quap <- function( flist , data , start , method="BFGS" , hessian=TRUE , debug=FA
             suppressWarnings(optim( par=pars , fn=make_minuslogl , flist=flist2 , data=data , veclist=veclist , hessian=hessian , method=method , ... ))
             , silent=TRUE
         )
-        if ( class(fit)=="try-error" ) {
+        if ( inherits(fit, "try-error") ) {
             # something went wrong...try to figure it out
             msg <- attr(fit,"condition")$message
             
@@ -503,7 +503,7 @@ quap <- function( flist , data , start , method="BFGS" , hessian=TRUE , debug=FA
     
     if ( hessian & dofit ) {
         vcov <- try( solve(fit$hessian) )
-        if ( class(vcov)[1]=="try-error" ) {
+        if ( inherits(vcov, "try-error") ) {
             warning( "Error when computing variance-covariance matrix (Hessian). Fit may not be reliable." )
             vcov <- matrix( NA , nrow=length(pars) , ncol=length(pars) )
         }