Measure_-class: An R6 object for measures

In ericdunipace/causalOT: Optimal Transport Weights for Causal Inference

An R6 object for measures

Description

Internal R6 class object for Measure objects

Public fields

balance_functions

the functions of the data that we want to adjust towards the targets

balance_target

the values the balance_functions are targeting

adapt

What aspect of the data will be adapted. One of "none","weights", or "x".

device

the torch::torch_device() of the data.

dtype

the torch::torch_dtype of the data.

n

the rows of the covariates, x.

d

the columns of the covariates, x.

probability_measure

is the measure a probability measure?

Active bindings

grad

gets or sets gradient

init_weights

returns the initial value of the weights

init_data

returns the initial value of the data

requires_grad

checks or turns on/off gradient

weights

gets or sets weights

x

Gets or sets the data.

Methods

Public methods

• Measure_$detach()

• Measure_$get_weight_parameters()

• Measure_$print()

• Measure_$new()

• Measure_$clone()

---

Method detach()

generates a deep clone of the object without gradients.

Usage

Measure_$detach()

---

Method get_weight_parameters()

Makes a copy of the weights parameters.

Usage

Measure_$get_weight_parameters()

---

Method print()

prints the measure object

Usage

Measure_$print(...)

Arguments

...

Not used

---

Method new()

Constructor function

Usage

Measure_$new(
  x,
  weights = NULL,
  probability.measure = TRUE,
  adapt = c("none", "weights", "x"),
  balance.functions = NA_real_,
  target.values = NA_real_,
  dtype = NULL,
  device = NULL
)

Arguments

x

The data points

weights

The empirical measure. If NULL, assigns equal weight to each observation

probability.measure

Is the empirical measure a probability measure? Default is TRUE.

adapt

Should we try to adapt the data ("x"), the weights ("weights"), or neither ("none"). Default is "none".

balance.functions

A matrix of functions of the covariates to target for mean balance. If NULL and target.values are provided, will use the data in x.

target.values

The targets for the balance functions. Should be the same length as columns in balance.functions.

dtype

The torch::torch_dtype or NULL.

device

The device to have the data on. Should be result of torch::torch_device() or NULL.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

Measure_$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

ericdunipace/causalOT documentation built on Aug. 8, 2024, 6:14 p.m.