R 2.10.0 - en to unknown language translation catalogue (374 entries)

en: 'acf' must be of length two or more
target: ‘acf’ must be of length two or more

en: 'alpha', 'beta' and 'gamma' must be within the unit interval.
target: 'alpha', ‘beta’ and ‘gamma’ must be within the unit interval.

en: 'x' must be numeric
target: ‘x’ must be numeric

en: 'which' specified no factors
target: ‘which’ specified no factors

en: 'which' specified some non-factors which will be dropped
target: ‘which’ specified some non-factors which will be dropped

en: 'lag.max' must be at least 0
target: ‘lag.max’ must be at least 0

en: 'lag.max' must be at least 1
target: ‘lag.max’ must be at least 1

en: NAs in 'x'
target: NAs in ‘x’

en: can use ci.type="ma" only if first lag is 0
target: can use ci.type=“ma” only if first lag is 0

en: no 'add1' method implemented for "mlm" models
target: no ‘add1’ method implemented for “mlm” models

en: no 'drop1' method for "mlm" models
target: no ‘drop1’ method for “mlm” models

en: F test assumes 'quasi%s' family
target: F test assumes ‘quasi%s’ family

en: AIC is not defined for this model, so 'step' cannot proceed
target: AIC is not defined for this model, so ‘step’ cannot proceed

en: 'A' must be an array or table
target: ‘A’ must be an array or table

en: 'by' must be a list
target: ‘by’ must be a list

en: 'FUN' must always return a scalar
target: ‘FUN’ must always return a scalar

en: 'x' must be coefficient matrix/data frame
target: ‘x’ must be coefficient matrix/data frame

en: option "show.coef.Pvalues" is invalid: assuming TRUE
target: option “show.coef.Pvalues” is invalid: assuming TRUE

en: 'P.values' is TRUE, but 'has.Pvalue' is not
target: ‘P.values’ is TRUE, but ‘has.Pvalue’ is not

en: option "show.signif.stars" is invalid: assuming TRUE
target: option “show.signif.stars” is invalid: assuming TRUE

en: 'anova' object must have colnames
target: ‘anova’ object must have colnames

en: 'conf.level' must be a single number between 0 and 1
target: ‘conf.level’ must be a single number between 0 and 1

en: not enough 'x' observations
target: not enough ‘x’ observations

en: not enough 'y' observations
target: not enough ‘y’ observations

en: 'formula' missing or incorrect
target: ‘formula’ missing or incorrect

en: the 'split' argument must be a list
target: the ‘split’ argument must be a list

en: unknown name(s) in the 'split' list
target: unknown name(s) in the ‘split’ list

en: 'coef' must define a contrast, i.e., sum to 0
target: ‘coef’ must define a contrast, i.e., sum to 0

en: 'coef' must have same length as 'contrast.obj'
target: ‘coef’ must have same length as ‘contrast.obj’

en: each element of '%s' must be logical
target: each element of ‘%s’ must be logical

en: columns of 'contrast.obj' must define a contrast (sum to zero)
target: columns of ‘contrast.obj’ must define a contrast (sum to zero)

en: 'object' does not include an error 'qr' component
target: ‘object’ does not include an error ‘qr’ component

en: columns of 'contrast.obj' must define a contrast(sum to zero)
target: columns of ‘contrast.obj’ must define a contrast(sum to zero)

en: collapsing to unique 'x' values
target: collapsing to unique ‘x’ values

en: 'approx' requires n >= 1
target: ‘approx’ requires n >= 1

en: 'vec' contains NAs
target: ‘vec’ contains NAs

en: 'vec' must be sorted non-decreasingly
target: ‘vec’ must be sorted non-decreasingly

en: 'order.max' must be >= 1
target: ‘order.max’ must be >= 1

en: 'order.max' must be < 'n.used'
target: ‘order.max’ must be < ‘n.used’

en: number of series in 'object' and 'newdata' do not match
target: number of series in ‘object’ and ‘newdata’ do not match

en: 'se.fit' not yet implemented for multivariate models
target: ‘se.fit’ not yet implemented for multivariate models

en: 'order.max' must be >= 0
target: ‘order.max’ must be >= 0

en: 'order' must be a non-negative numeric vector of length 3
target: ‘order’ must be a non-negative numeric vector of length 3

en: 'seasonal' must be a list with component 'order'
target: ‘seasonal’ must be a list with component ‘order’

en: 'seasonal$order' must be a non-negative numeric vector of length 3
target: ‘seasonal$order’ must be a non-negative numeric vector of length 3

en: lengths of 'x' and 'xreg' do not match
target: lengths of ‘x’ and ‘xreg’ do not match

en: wrong length for 'fixed'
target: wrong length for ‘fixed’

en: 'init' is of the wrong length
target: ‘init’ is of the wrong length

en: 'xreg' and 'newxreg' have different numbers of columns
target: ‘xreg’ and ‘newxreg’ have different numbers of columns

en: 'xreg' is collinear
target: ‘xreg’ is collinear

en: NAs present: setting 'delta' to -1
target: NAs present: setting ‘delta’ to -1

en: invalid 'x'
target: invalid ‘x’

en: 'x' must be a list with at least 2 elements
target: ‘x’ must be a list with at least 2 elements

en: 'x' and 'g' must have the same length
target: ‘x’ and ‘g’ must have the same length

en: 'x' must be nonnegative and integer
target: ‘x’ must be nonnegative and integer

en: 'n' must be a positive integer >= 'x'
target: ‘n’ must be a positive integer >= ‘x’

en: incorrect length of 'x'
target: incorrect length of ‘x’

en: 'p' must be a single number between 0 and 1
target: ‘p’ must be a single number between 0 and 1

en: object '%s' has no scores
target: object ‘%s’ has no scores

en: 'scale' is outside [0, 1]
target: ‘scale’ is outside [0, 1]

en: unequal number of rows in 'cancor'
target: unequal number of rows in ‘cancor’

en: dimension 0 in 'x' or 'y'
target: dimension 0 in ‘x’ or ‘y’

en: 'x' has rank 0
target: ‘x’ has rank 0

en: 'y' has rank 0
target: ‘y’ has rank 0

en: 'x' and 'y' must have the same length
target: ‘x’ and ‘y’ must have the same length

en: 'x' and 'y' must have at least 2 levels
target: ‘x’ and ‘y’ must have at least 2 levels

en: all entries of 'x' must be nonnegative and finite
target: all entries of ‘x’ must be nonnegative and finite

en: at least one entry of 'x' must be positive
target: at least one entry of ‘x’ must be positive

en: 'x' must at least have 2 elements
target: ‘x’ must at least have 2 elements

en: 'x' and 'p' must have the same number of elements
target: ‘x’ and ‘p’ must have the same number of elements

en: NA values not allowed in 'd'
target: NA values not allowed in ‘d’

en: distances must be result of 'dist' or a square matrix
target: distances must be result of ‘dist’ or a square matrix

en: 'k' must be in {1, 2, ..  n - 1}
target: ‘k’ must be in {1, 2, ..  n - 1}

en: 'scores' argument is of the wrong length
target: ‘scores’ argument is of the wrong length

en: 'scores' must all be different numbers
target: ‘scores’ must all be different numbers

en: 'degree' must be at least 1
target: ‘degree’ must be at least 1

en: missing values are not allowed in 'poly'
target: missing values are not allowed in ‘poly’

en: 'degree' must be less than number of unique points
target: ‘degree’ must be less than number of unique points

en: contr*(.., sparse=TRUE) needs package "Matrix" correctly installed
target: contr*(.., sparse=TRUE) needs package “Matrix” correctly installed

en: supply both 'x' and 'y' or a matrix-like 'x'
target: supply both ‘x’ and ‘y’ or a matrix-like ‘x’

en: 'x' is empty
target: ‘x’ is empty

en: both 'x' and 'y' must be non-empty
target: both ‘x’ and ‘y’ must be non-empty

en: cannot handle 'pairwise.complete.obs'
target: cannot handle ‘pairwise.complete.obs’

en: 'V' is not a square numeric matrix
target: ‘V’ is not a square numeric matrix

en: 'formula' missing or invalid
target: ‘formula’ missing or invalid

en: 'x' must be a matrix or a data frame
target: ‘x’ must be a matrix or a data frame

en: 'x' must contain finite values only
target: ‘x’ must contain finite values only

en: length of 'wt' must equal the number of rows in 'x'
target: length of ‘wt’ must equal the number of rows in ‘x’

en: length of 'center' must equal the number of columns in 'x'
target: length of ‘center’ must equal the number of columns in ‘x’

en: invalid 'tree' (merge component)
target: invalid ‘tree’ (merge component)

en: either 'k' or 'h' must be specified
target: either ‘k’ or ‘h’ must be specified

en: the 'height' component of 'tree' is not sorted
    (increasingly); consider applying as.hclust() first
target: the ‘height’ component of ‘tree’ is not sorted
    (increasingly); consider applying as.hclust() first

en: elements of 'k' must be between 1 and %d
target: elements of ‘k’ must be between 1 and %d

en: 'merge' and 'height' do not fit!
target: ‘merge’ and ‘height’ do not fit!

en: 'order.dendrogram' requires a dendrogram
target: ‘order.dendrogram’ requires a dendrogram

en: 'X' is not a dendrogram
target: ‘X’ is not a dendrogram

en: 'x' must be a numeric matrix
target: ‘x’ must be a numeric matrix

en: 'x' must have at least 2 rows and 2 columns
target: ‘x’ must have at least 2 rows and 2 columns

en: 'margins' must be a numeric vector of length 2
target: ‘margins’ must be a numeric vector of length 2

en: Colv = "Rowv" but nrow(x) != ncol(x)
target: Colv = “Rowv” but nrow(x) != ncol(x)

en: 'ColSideColors' must be a character vector of length ncol(x)
target: ‘ColSideColors’ must be a character vector of length ncol(x)

en: 'RowSideColors' must be a character vector of length nrow(x)
target: ‘RowSideColors’ must be a character vector of length nrow(x)

en: argument 'x' must be numeric
target: argument ‘x’ must be numeric

en: 'x' contains missing values
target: ‘x’ contains missing values

en: 'x' and 'weights' have unequal length
target: ‘x’ and ‘weights’ have unequal length

en: 'weights' must all be finite
target: ‘weights’ must all be finite

en: 'weights' must not be negative
target: ‘weights’ must not be negative

en: non-finite 'bw'
target: non-finite ‘bw’

en: 'bw' is not positive.
target: ‘bw’ is not positive.

en: non-finite 'from'
target: non-finite ‘from’

en: non-finite 'to'
target: non-finite ‘to’

en: 'x' is not a vector
target: ‘x’ is not a vector

en: bad value for 'lag' or 'differences'
target: bad value for ‘lag’ or ‘differences’

en: 'xi' has not the right length
target: ‘xi’ has not the right length

en: incorrect dimensions for 'xi'
target: incorrect dimensions for ‘xi’

en: 'x' is not a vector or matrix
target: ‘x’ is not a vector or matrix

en: 'x' must be non-negative
target: ‘x’ must be non-negative

en: 'prob' and 'mu' both specified
target: ‘prob’ and ‘mu’ both specified

en: 'x' must have 1 or more non-missing values
target: ‘x’ must have 1 or more non-missing values

en: 'covmat' is not a valid covariance list
target: ‘covmat’ is not a valid covariance list

en: neither 'x' nor 'covmat' supplied
target: neither ‘x’ nor ‘covmat’ supplied

en: 'covmat' is of unknown type
target: ‘covmat’ is of unknown type

en: requested scores without an 'x' matrix
target: requested scores without an ‘x’ matrix

en: 'start' must have %d rows
target: ‘start’ must have %d rows

en: invalid argument 'lambda'
target: invalid argument ‘lambda’

en: link "%s" not available for poisson family; available links are %s
target: link “%s” not available for poisson family; available links are %s

en: link "%s" not available for quasipoisson family; available links are %s
target: link “%s” not available for quasipoisson family; available links are %s

en: link "%s" not available for gaussian family; available links are %s
target: link “%s” not available for gaussian family; available links are %s

en: link "%s" not available for binomial family; available links are %s
target: link “%s” not available for binomial family; available links are %s

en: link "%s" not available for quasibinomial family; available links are %s
target: link “%s” not available for quasibinomial family; available links are %s

en: link "%s" not available for gamma family; available links are %s
target: link “%s” not available for gamma family; available links are %s

en: link "%s" not available for inverse.gaussian family; available links are %s
target: link “%s” not available for inverse.gaussian family; available links are %s

en: Need CRAN package 'SuppDists' for 'inverse.gaussian' family
target: Need CRAN package ‘SuppDists’ for ‘inverse.gaussian’ family

en: 'variance' "%s" is invalid: possible values are "mu(1-mu)", "mu", "mu^2", "mu^3" and "constant"
target: ‘variance’ “%s” is invalid: possible values are “mu(1-mu)”, “mu”, “mu^2”, “mu^3” and “constant”

en: missing values in 'filter'
target: missing values in ‘filter’

en: 'filter' is longer than time series
target: ‘filter’ is longer than time series

en: argument 'sides' must be 1 or 2
target: argument ‘sides’ must be 1 or 2

en: length of 'init' must equal length of 'filter'
target: length of ‘init’ must equal length of ‘filter’

en: 'x' must have at least 2 rows and columns
target: ‘x’ must have at least 2 rows and columns

en: 'x' has entries too large to be integer
target: ‘x’ has entries too large to be integer

en: 'x' has been rounded to integer:
target: ‘x’ has been rounded to integer:

en: if 'x' is not a matrix, 'y' must be given
target: if ‘x’ is not a matrix, ‘y’ must be given

en: 'mult' must be integer >= 2, typically = 30
target: ‘mult’ must be integer >= 2, typically = 30

en: alternative must be "two.sided", "less" or "greater"
target: alternative must be “two.sided”, “less” or “greater”

en: 'or' must be a single number between 0 and Inf
target: ‘or’ must be a single number between 0 and Inf

en: 'hybrid' is ignored for a 2 x 2 table
target: ‘hybrid’ is ignored for a 2 x 2 table

en: incorrect specification for 'formula'
target: incorrect specification for ‘formula’

en: incorrect specification for 'row.vars'
target: incorrect specification for ‘row.vars’

en: incorrect specification for 'col.vars'
target: incorrect specification for ‘col.vars’

en: 'formula' must have both left and right hand sides
target: ‘formula’ must have both left and right hand sides

en: 'formula' has '.' in both left and right hand side
target: ‘formula’ has ‘.’ in both left and right hand side

en: 'x' must be an "ftable" object
target: ‘x’ must be an “ftable” object

en: 'file' must be a character string or connection
target: ‘file’ must be a character string or connection

en: 'row.var.names' missing
target: ‘row.var.names’ missing

en: 'col.vars' missing or incorrect
target: ‘col.vars’ missing or incorrect

en: 'family' not recognized
target: ‘family’ not recognized

en: invalid 'method'
target: invalid ‘method’

en: 'weights' must be a numeric vector
target: ‘weights’ must be a numeric vector

en: value of 'epsilon' must be > 0
target: value of ‘epsilon’ must be > 0

en: 'family' argument seems not to be a valid family object
target: ‘family’ argument seems not to be a valid family object

en: length of 'start' should equal %d and correspond to initial coefs for %s
target: length of ‘start’ should equal %d and correspond to initial coefs for %s

en: the following arguments to 'anova.glm' are invalid and dropped:
target: the following arguments to ‘anova.glm’ are invalid and dropped:

en: using F test with a '%s' family is inappropriate
target: using F test with a ‘%s’ family is inappropriate

en: 'merge' component in dendrogram must be integer
target: ‘merge’ component in dendrogram must be integer

en: argument 'x' cannot be coerced to class "hclust"
target: argument ‘x’ cannot be coerced to class “hclust”

en: 'k' and 'h' must be a scalar
target: ‘k’ and ‘h’ must be a scalar

en: specify exactly one of 'k' and 'h'
target: specify exactly one of ‘k’ and ‘h’

en: specify exactly one of 'which' and 'x'
target: specify exactly one of ‘which’ and ‘x’

en: all elements of 'which' must be between 1 and %d
target: all elements of ‘which’ must be between 1 and %d

en: 'r' is less than 1
target: ‘r’ is less than 1

en: 'm' is less than 1
target: ‘m’ is less than 1

en: 'r' is less than 0
target: ‘r’ is less than 0

en: 'm' must be numeric with non-negative integers
target: ‘m’ must be numeric with non-negative integers

en: 'coef' must be a vector
target: ‘coef’ must be a vector

en: 'coef' does not have the correct length
target: ‘coef’ does not have the correct length

en: 'k' is not a kernel
target: ‘k’ is not a kernel

en: 'x' is shorter than kernel 'k'
target: ‘x’ is shorter than kernel ‘k’

en: 'kernapply' is not available for object 'x'
target: ‘kernapply’ is not available for object ‘x’

en: 'x' is not a kernel
target: ‘x’ is not a kernel

en: 'centers' must be a number or a matrix
target: ‘centers’ must be a number or a matrix

en: 'iter.max' must be positive
target: ‘iter.max’ must be positive

en: must have same number of columns in 'x' and 'centers'
target: must have same number of columns in ‘x’ and ‘centers’

en: not enough 'x' data
target: not enough ‘x’ data

en: not enough 'y' data
target: not enough ‘y’ data

en: 'y' must be numeric or a string naming a valid function
target: ‘y’ must be numeric or a string naming a valid function

en: 'k' is not an integer
target: ‘k’ is not an integer

en: method = '%s' is not supported. Using 'qr'
target: method = ‘%s’ is not supported. Using ‘qr’

en: 'x' must be a matrix
target: ‘x’ must be a matrix

en: invalid 'lm' object:  no 'terms' nor 'qr' component
target: invalid ‘lm’ object:  no ‘terms’ nor ‘qr’ component

en: residual degrees of freedom in object suggest this is not an "lm" fit
target: residual degrees of freedom in object suggest this is not an “lm” fit

en: 'weights' as formula should be one-sided
target: ‘weights’ as formula should be one-sided

en: 'object' has no 'effects' component
target: ‘object’ has no ‘effects’ component

en: the 'se.fit' argument is not yet implemented for "mlm" objects
target: the ‘se.fit’ argument is not yet implemented for “mlm” objects

en: 'degree' must be 0, 1 or 2
target: ‘degree’ must be 0, 1 or 2

en: both 'span' and 'enp.target' specified: 'span' will be used
target: both ‘span’ and ‘enp.target’ specified: ‘span’ will be used

en: invalid 'control' argument
target: invalid ‘control’ argument

en: invalid 'y'
target: invalid ‘y’

en: first argument must be a "loess" object
target: first argument must be a “loess” object

en: 'start' and 'table' must be same length
target: ‘start’ and ‘table’ must be same length

en: incorrect specification of 'table' or 'start'
target: incorrect specification of ‘table’ or ‘start’

en: 'X' matrix has %d responses, 'Y' has %d responses
target: ‘X’ matrix has %d responses, ‘Y’ has %d responses

en: 'X' matrix was collinear
target: ‘X’ matrix was collinear

en: 'low' and 'high' cannot be both TRUE
target: ‘low’ and ‘high’ cannot be both TRUE

en: object must be of class "manova" or "maov"
target: object must be of class “manova” or “maov”

en: 'x' must be a 3-dimensional array
target: ‘x’ must be a 3-dimensional array

en: if 'x' is not an array, 'y' must be given
target: if ‘x’ is not an array, ‘y’ must be given

en: if 'x' is not an array, 'z' must be given
target: if ‘x’ is not an array, ‘z’ must be given

en: 'x', 'y', and 'z' must have the same length
target: 'x', 'y', and ‘z’ must have the same length

en: 'x' must be square with at least two rows and columns
target: ‘x’ must be square with at least two rows and columns

en: 'x' and 'y' must have the same number of levels (minimum 2)
target: ‘x’ and ‘y’ must have the same number of levels (minimum 2)

en: 'mlm' objects with weights are not supported
target: ‘mlm’ objects with weights are not supported

en: 'model.tables' is not implemented for multiple responses
target: ‘model.tables’ is not implemented for multiple responses

en: type '%s' is not implemented yet
target: type ‘%s’ is not implemented yet

en: this fit does not inherit from "lm"
target: this fit does not inherit from “lm”

en: 'cterms' argument must match terms in model object
target: ‘cterms’ argument must match terms in model object

en: SEs for type '%s' are not yet implemented
target: SEs for type ‘%s’ are not yet implemented

en: 'termlabels' must be a character vector of length at least one
target: ‘termlabels’ must be a character vector of length at least one

en: 'termobj' must be a object of class "terms"
target: ‘termobj’ must be a object of class “terms”

en: variable '%s' was fitted with type "%s" but type "%s" was supplied
target: variable ‘%s’ was fitted with type “%s” but type “%s” was supplied

en: 'data' must be a data.frame, not a matrix or an array
target: ‘data’ must be a data.frame, not a matrix or an array

en: 'newdata' had %d rows but variable(s) found have %d rows
target: ‘newdata’ had %d rows but variable(s) found have %d rows

en: character variable '%s' changed to a factor
target: character variable ‘%s’ changed to a factor

en: variable '%s' is not a factor
target: variable ‘%s’ is not a factor

en: factor '%s' has new level(s) %s
target: factor ‘%s’ has new level(s) %s

en: 'offset' must be numeric
target: ‘offset’ must be numeric

en: variable '%s' converted to a factor
target: variable ‘%s’ converted to a factor

en: invalid 'contrasts.arg' argument
target: invalid ‘contrasts.arg’ argument

en: variable '%s' is absent, its contrast will be ignored
target: variable ‘%s’ is absent, its contrast will be ignored

en: using type="numeric" with a factor response will be ignored
target: using type=“numeric” with a factor response will be ignored

en: invalid 'data' argument
target: invalid ‘data’ argument

en: invalid argument 'omit'
target: invalid argument ‘omit’

en: 'print.level' must be in {0,1,2}
target: ‘print.level’ must be in {0,1,2}

en: 'interval' must be a vector of length 2
target: ‘interval’ must be a vector of length 2

en: Logical `hessian' argument not allowed.  See documentation.
target: Logical ‘hessian’ argument not allowed.  See documentation.

en: 'params' has wrong length
target: ‘params’ has wrong length

en: 'varying' must be in seq_along(pars)
target: ‘varying’ must be in seq_along(pars)

en: 'varying' has wrong length
target: ‘varying’ has wrong length

en: 'varying' must be logical, integer or character
target: ‘varying’ must be logical, integer or character

en: invalid argument to 'getProfile'
target: invalid argument to ‘getProfile’

en: setVarying : 'vary' length must match length of parameters
target: setVarying : ‘vary’ length must match length of parameters

en: 'data' must be a list or an environment
target: ‘data’ must be a list or an environment

en: Consider specifying 'start' or using a selfStart model
target: Consider specifying ‘start’ or using a selfStart model

en: argument 'subset' will be ignored
target: argument ‘subset’ will be ignored

en: argument 'na.action' will be ignored
target: argument ‘na.action’ will be ignored

en: Upper or lower bounds ignored unless algorithm = "port"
target: Upper or lower bounds ignored unless algorithm = “port”

en: cannot calculate REML log-likelihood for "nls" objects
target: cannot calculate REML log-likelihood for “nls” objects

en: anova is only defined for sequences of "nls" objects
target: anova is only defined for sequences of “nls” objects

en: 'anova' is only defined for sequences of "nls" objects
target: ‘anova’ is only defined for sequences of “nls” objects

en: formula '%s' must be of the form '~expr'
target: formula ‘%s’ must be of the form ‘~expr’

en: '%s' cannot be of mode '%s'
target: ‘%s’ cannot be of mode ‘%s’

en: read the documentation for 'trace' more carefully
target: read the documentation for ‘trace’ more carefully

en: 'trace != 0' needs 'REPORT >= 1'
target: ‘trace != 0’ needs ‘REPORT >= 1’

en: method L-BFGS-B uses 'factr' (and 'pgtol') instead of 'reltol' and 'abstol'
target: method L-BFGS-B uses ‘factr’ (and 'pgtol') instead of ‘reltol’ and ‘abstol’

en: 'x' must have 2 columns
target: ‘x’ must have 2 columns

en: 'x' and 'n' must have the same length
target: ‘x’ and ‘n’ must have the same length

en: use only with "lm" objects
target: use only with “lm” objects

en: 'which' must be in 1:6
target: ‘which’ must be in 1:6

en: 'id.n' must be in {1,..,%d}
target: ‘id.n’ must be in {1,..,%d}

en: 'x' and 'T' have incompatible length
target: ‘x’ and ‘T’ have incompatible length

en: 'x' must be finite, nonnegative, and integer
target: ‘x’ must be finite, nonnegative, and integer

en: 'T' must be nonnegative
target: ‘T’ must be nonnegative

en: 'r' must be a single positive number
target: ‘r’ must be a single positive number

en: exactly one of 'n', 'delta', 'sd', 'power', and 'sig.level' must be NULL
target: exactly one of 'n', 'delta', 'sd', 'power', and ‘sig.level’ must be NULL

en: 'sig.level' must be numeric in [0, 1]
target: ‘sig.level’ must be numeric in [0, 1]

en: exactly one of 'n', 'p1', 'p2', 'power', and 'sig.level' must be NULL
target: exactly one of 'n', 'p1', 'p2', 'power', and ‘sig.level’ must be NULL

en: exactly one of 'groups', 'n', 'between.var', 'within.var', 'power', and 'sig.level' must be NULL
target: exactly one of 'groups', 'n', 'between.var', 'within.var', 'power', and ‘sig.level’ must be NULL

en: 'nterms' is missing with no default
target: ‘nterms’ is missing with no default

en: 'ppr' applies only to numerical variables
target: ‘ppr’ applies only to numerical variables

en: mismatched 'x' and 'y'
target: mismatched ‘x’ and ‘y’

en: wrong number of columns in 'x'
target: wrong number of columns in ‘x’

en: no scores are available: refit with 'retx=TRUE'
target: no scores are available: refit with ‘retx=TRUE’

en: 'newdata' must be a matrix or data frame
target: ‘newdata’ must be a matrix or data frame

en: 'newdata' does not have named columns matching one or more of the original columns
target: ‘newdata’ does not have named columns matching one or more of the original columns

en: 'newdata' does not have the correct number of columns
target: ‘newdata’ does not have the correct number of columns

en: both 'x' and 'covmat' were supplied: 'x' will be ignored
target: both ‘x’ and ‘covmat’ were supplied: ‘x’ will be ignored

en: 'princomp' can only be used with more units than variables
target: ‘princomp’ can only be used with more units than variables

en: argument does not include a 'qr' component
target: argument does not include a ‘qr’ component

en: argument does not include an 'effects' component
target: argument does not include an ‘effects’ component

en: 'proj' is not implemented for "mlm" fits
target: ‘proj’ is not implemented for “mlm” fits

en: 'proj' is not implemented for multiple responses
target: ‘proj’ is not implemented for multiple responses

en: elements of 'n' must be positive
target: elements of ‘n’ must be positive

en: elements of 'x' must be nonnegative
target: elements of ‘x’ must be nonnegative

en: elements of 'x' must not be greater than those of 'n'
target: elements of ‘x’ must not be greater than those of ‘n’

en: 'p' must have the same length as 'x' and 'n'
target: ‘p’ must have the same length as ‘x’ and ‘n’

en: elements of 'p' must be in (0,1)
target: elements of ‘p’ must be in (0,1)

en: NA's are not allowed in 'groups' or 'blocks'
target: NA's are not allowed in ‘groups’ or ‘blocks’

en: 'y', 'groups' and 'blocks' must have the same length
target: 'y', ‘groups’ and ‘blocks’ must have the same length

en: 'formula' missing
target: ‘formula’ missing

en: missing values and NaN's not allowed if 'na.rm' is FALSE
target: missing values and NaN's not allowed if ‘na.rm’ is FALSE

en: 'probs' outside [0,1]
target: ‘probs’ outside [0,1]

en: invalid argument 'n'
target: invalid argument ‘n’

en: invalid argument 'r'
target: invalid argument ‘r’

en: invalid argument 'c'
target: invalid argument ‘c’

en: arguments 'r' and 'c' must have the same sums
target: arguments ‘r’ and ‘c’ must have the same sums

en: 'relevel' only for factors
target: ‘relevel’ only for factors

en: 'ref' must be an existing level
target: ‘ref’ must be an existing level

en: 'varying' arguments must be the same length
target: ‘varying’ arguments must be the same length

en: 'times' is wrong length
target: ‘times’ is wrong length

en: no 'reshapeWide' attribute, must specify 'varying'
target: no ‘reshapeWide’ attribute, must specify ‘varying’

en: 'varying' must be nonempty list or vector
target: ‘varying’ must be nonempty list or vector

en: 'k' must be positive
target: ‘k’ must be positive

en: 'k' must be odd!  Changing 'k' to
target: ‘k’ must be odd!  Changing ‘k’ to

en: 'k' is bigger than 'n'!  Changing 'k' to
target: ‘k’ is bigger than 'n'!  Changing ‘k’ to

en: bandwidth 'k' must be >= 1 and odd!
target: bandwidth ‘k’ must be >= 1 and odd!

en: argument 'object' has an impossible length
target: argument ‘object’ has an impossible length

en: no 'getInitial' method found for "%s" objects
target: no ‘getInitial’ method found for “%s” objects

en: all 'x' values are identical
target: all ‘x’ values are identical

en: 'nknots' must be numeric <= n
target: ‘nknots’ must be numeric <= n

en: cannot use more inner knots than unique 'x' values
target: cannot use more inner knots than unique ‘x’ values

en: invalid 'control.spar'
target: invalid ‘control.spar’

en: lengths of 'x' and 'w' must match
target: lengths of ‘x’ and ‘w’ must match

en: need at least four unique 'x' values
target: need at least four unique ‘x’ values

en: crossvalidation with non-unique 'x' values seems doubtful
target: crossvalidation with non-unique ‘x’ values seems doubtful

en: NA lev[]; probably smoothing parameter 'spar' way too large!
target: NA lev[]; probably smoothing parameter ‘spar’ way too large!

en: type = "partial" is not yet implemented
target: type = “partial” is not yet implemented

en: not a valid "smooth.spline" object
target: not a valid “smooth.spline” object

en: 'y' must be numeric vector
target: ‘y’ must be numeric vector

en: number of observations in 'x' and 'y' must match.
target: number of observations in ‘x’ and ‘y’ must match.

en: 'span' must be between 0 and 1.
target: ‘span’ must be between 0 and 1.

en: 'x' must be between 0 and 1 for periodic smooth
target: ‘x’ must be between 0 and 1 for periodic smooth

en: 'p' must be between 0 and 0.5
target: ‘p’ must be between 0 and 0.5

en: length of 'p' must be 1 or equal the number of columns of 'x'
target: length of ‘p’ must be 1 or equal the number of columns of ‘x’

en: 'x' must be a time series or an ar() fit
target: ‘x’ must be a time series or an ar() fit

en: must specify 'spans' or a valid kernel
target: must specify ‘spans’ or a valid kernel

en: 'spline' requires n >= 1
target: ‘spline’ requires n >= 1

en: 'deriv' must be between 0 and 3
target: ‘deriv’ must be between 0 and 3

en: 'deriv' must be between 0 and 2
target: ‘deriv’ must be between 0 and 2

en: 'x' must be *strictly* increasing (non - NA)
target: ‘x’ must be *strictly* increasing (non - NA)

en: stepfun: 'x' must be ordered increasingly
target: stepfun: ‘x’ must be ordered increasingly

en: 'x' must have length >= 1
target: ‘x’ must have length >= 1

en: 'y' must be one longer than 'x'
target: ‘y’ must be one longer than ‘x’

en: no 'as.stepfun' method available for 'x'
target: no ‘as.stepfun’ method available for ‘x’

en: 'plot.stepfun' called with wrong type of argument 'x'
target: ‘plot.stepfun’ called with wrong type of argument ‘x’

en: 'cutpoints' must be unique in 0 < cuts < 1, but are =
target: ‘cutpoints’ must be unique in 0 < cuts < 1, but are =

en: 'cutpoints' must be unique, but are =
target: ‘cutpoints’ must be unique, but are =

en: 'x' must be between -1 and 1
target: ‘x’ must be between -1 and 1

en: 'x' must be between %s and %s
target: ‘x’ must be between %s and %s

en: number of 'cutpoints' must be one less than number of symbols
target: number of ‘cutpoints’ must be one less than number of symbols

en: number of 'cutpoints' must be one more than number of symbols
target: number of ‘cutpoints’ must be one more than number of symbols

en: must have 2 'symbols' for logical 'x' argument
target: must have 2 ‘symbols’ for logical ‘x’ argument

en: invalid 'abbr.colnames'
target: invalid ‘abbr.colnames’

en: 'mu' must be a single number
target: ‘mu’ must be a single number

en: 'y' is missing for paired test
target: ‘y’ is missing for paired test

en: 'main' must be TRUE, FALSE, NULL or character (vector).
target: ‘main’ must be TRUE, FALSE, NULL or character (vector).

en: 'ts' object must have one or more observations
target: ‘ts’ object must have one or more observations

en: 'start' cannot be after 'end'
target: ‘start’ cannot be after ‘end’

en: series is corrupt, with no 'tsp' attribute
target: series is corrupt, with no ‘tsp’ attribute

en: series is corrupt: length %d with 'tsp' implying %d
target: series is corrupt: length %d with ‘tsp’ implying %d

en: cannot plot more than 10 series as "multiple"
target: cannot plot more than 10 series as “multiple”

en: 'xy.labels' must be logical or character
target: ‘xy.labels’ must be logical or character

en: 'frequency' and 'deltat' are both supplied and are inconsistent
target: ‘frequency’ and ‘deltat’ are both supplied and are inconsistent

en: bad value for 'start'
target: bad value for ‘start’

en: 'start' value not changed
target: ‘start’ value not changed

en: bad value for 'end'
target: bad value for ‘end’

en: 'end' value not changed
target: ‘end’ value not changed

en: 'start' > 'end'
target: ‘start’ > ‘end’

en: 'model' must be list
target: ‘model’ must be list

en: 'ar' part of model is not stationary
target: ‘ar’ part of model is not stationary

en: burn-in 'n.start' must be as long as 'ar + ma'
target: burn-in ‘n.start’ must be as long as ‘ar + ma’

en: 'model$order' must be of length 3
target: ‘model$order’ must be of length 3

en: inconsistent specification of 'ar' order
target: inconsistent specification of ‘ar’ order

en: inconsistent specification of 'ma' order
target: inconsistent specification of ‘ma’ order

en: 'start.innov' is too short: need %d points
target: ‘start.innov’ is too short: need %d points

en: 'ratio' must be a single positive number
target: ‘ratio’ must be a single positive number

en: 'x' and 'w' must have the same length
target: ‘x’ and ‘w’ must have the same length

en: 'y' must be numeric
target: ‘y’ must be numeric

en: not enough (finite) 'x' observations
target: not enough (finite) ‘x’ observations

en: must supply either 'formula' or 'data'
target: must supply either ‘formula’ or ‘data’

en: xtabs(*, sparse=TRUE) needs package "Matrix" correctly installed
target: xtabs(*, sparse=TRUE) needs package “Matrix” correctly installed

en: too few distinct input values to fit the 'asympOff' model
target: too few distinct input values to fit the ‘asympOff’ model

en: too few distinct input values to fit the 'asympOrig' model
target: too few distinct input values to fit the ‘asympOrig’ model

en: must have length of response = length of second argument to 'SSfol'
target: must have length of response = length of second argument to ‘SSfol’

en: must have at least 4 observations to fit an 'SSfol' model
target: must have at least 4 observations to fit an ‘SSfol’ model

en: all 'x' values must be non-negative to fit the Weibull growth model
target: all ‘x’ values must be non-negative to fit the Weibull growth model
