Cross product of transpose of matrix in R, you’ll learn how to calculate matrix cross products using the `crossprod`

and `tcrossprod`

functions.

The cross product of a matrix and its transpose is a fundamental concept in linear algebra, and it is often used in various applications such as machine learning, data analysis, and statistics.

In R, the cross product of a matrix and its transpose can be calculated using the `tcrossprod()`

function, which is a more efficient and convenient way to compute the result compared to using the `t()`

function and the `%*%`

operator.

We will also provide examples of how to use this function in practice, and discuss the advantages and by the end of this tutorial, you will have a solid understanding of how to calculate the cross product of a matrix and its transpose in R, and how to apply this knowledge in your own projects.

**Example 1: Cross Product Using crossprod Function**

Create example data:

```
my_mat <- matrix(1:9, nrow = 3)
my_mat
[,1] [,2] [,3]
[1,] 1 4 7
[2,] 2 5 8
[3,] 3 6 9
my_vec <- 1:3
```

Calculate cross product using `crossprod`

function:

```
my_crossprod1 <- crossprod(my_mat, my_vec)
my_crossprod1
```

Result:

```
[,1]
[1,] 14
[2,] 32
[3,] 50
```

**Example 2: Cross Product of Transpose of Matrix Using tcrossprod Function**

What is the best way to filter by row number in R? » Data Science Tutorials

Calculate cross product of transpose of matrix using `tcrossprod`

function:

```
my_tcrossprod1 <- tcrossprod(my_mat)
my_tcrossprod1
```

Result:

```
[,1] [,2] [,3]
[1,] 66 78 90
[2,] 78 93 108
[3,] 90 108 126
```

Note that the same result can be obtained using the `%*%`

operator and `t`

function:

```
my_tcrossprod2 <- my_mat %*% t(my_mat)
my_tcrossprod2
```

Result:

```
[,1] [,2] [,3]
[1,] 66 78 90
[2,] 78 93 108
[3,] 90 108 126
```