## Bias estimation and calibration

estimate_bias()

Estimate bias from control measurements

calibrate()

Calibrate a relative-abundance matrix by a bias vector

cooccurrence_matrix() cooccurrence_network() cooccurrence_components()

Taxon co-occurrence network

## Compositional-data computations

perturb()

Compositionally perturb a relative-abundance matrix

pairwise_ratios()

Pairwise ratios of vector elements and matrix rows or columns

compute_ratios()

Compute taxon ratios from a tidy data frame

center()

Compute the center (compositional mean) of a set of compositions

bootrep_center()

Generate bootstrap replicates of the sample center

center_elts()

Geometrically center the elements of x

close_elts()

Close the elements of x to proportions

clr()

Compute the centered log-ratio transform of x

logit()

Logit (log-odds) of the probability vector x

odds()

Odds of the probability vector x

anorm()

Aitchison norm of x

xydist()

Distance or dissimilarity between relative abundance vectors x and y

gm()

Geometric (multiplicative) version of the function f

gm_abs()

Geometric absolute value of x

gm_mean()

Geometric mean of x

gm_range()

Geometric range of x

gm_sd()

Geometric standard deviation of x

## Data-frame manipulation and coercion

as_matrix()

Coerce a (wide) data frame to a matrix

build_matrix()

Create a matrix from columns of a tidy data frame

mutate_by()

Mutate within groups