wdX

C++ Function Reference

1 Signature

Eigen::MatrixXd BigDataStatMeth::wdX(const Eigen::MatrixXd &X, const Eigen::VectorXd &w)

2 Description

Compute diagonal-matrix product wX.

3 Parameters

X (const Eigen::MatrixXd &): Input matrix
w (const Eigen::VectorXd &): Vector representing diagonal matrix

4 Returns

Diagonal-matrix product wX

5 Details

Computes the product of a diagonal matrix (represented as a vector) with a matrix using sequential processing.

6 Source Code

Implementation

File: inst/include/memAlgebra/memOptimizedProducts.hpp • Lines 262-271

inline Eigen::MatrixXd wdX(const Eigen::MatrixXd& X, const Eigen::VectorXd& w)
{
    int n = X.cols();
    Eigen::MatrixXd C = Eigen::MatrixXd::Zero(X.rows(),n) ; 
    
    for (int i=0; i<n; i++) {
        C.row(i) = w(i)*X.row(i);
    }
    return(C);
}

7 Usage Example

#include "BigDataStatMeth.hpp"

// Example usage
auto result = wdX(...);

---
title: "wdX"
subtitle: "C++ Function Reference"
---

## Signature

```cpp
Eigen::MatrixXd BigDataStatMeth::wdX(const Eigen::MatrixXd &X, const Eigen::VectorXd &w)
```

## Description

Compute diagonal-matrix product wX.

## Parameters

- `X` (`const Eigen::MatrixXd &`): Input matrix
- `w` (`const Eigen::VectorXd &`): Vector representing diagonal matrix

## Returns

Diagonal-matrix product wX

## Details

Computes the product of a diagonal matrix (represented as a vector) with a matrix using sequential processing.

## Source Code

::: {.callout-note collapse="true"}
### Implementation

**File:** `inst/include/memAlgebra/memOptimizedProducts.hpp` • **Lines 262-271**

```cpp
inline Eigen::MatrixXd wdX(const Eigen::MatrixXd& X, const Eigen::VectorXd& w)
{
    int n = X.cols();
    Eigen::MatrixXd C = Eigen::MatrixXd::Zero(X.rows(),n) ; 
    
    for (int i=0; i<n; i++) {
        C.row(i) = w(i)*X.row(i);
    }
    return(C);
}
```
:::

## Usage Example

```cpp
#include "BigDataStatMeth.hpp"

// Example usage
auto result = wdX(...);
```