Diag "Hat" matrix

Hi R users:

What is the difference between in the computation of the diag of the
"hat" matrix in:
"lm.influence" and the matrix operations with "solve()" and "t()"?

I mean, this is my X matrix

        x1    x2    x3    x4     x5
 [1,] 0.297 0.310 0.290 0.220 0.1560

[16,] 0.378 0.420 0.380 0.281 0.2000

If I use:
diag(X%*%solve(t(X)%*%X)%*%t(X))
I obtain:
 [1] 0.15248181 0.27102872 0.11476375 0.12941386 0.90455886 0.32246292
 [7] 0.43858581 0.16533854 0.37415984 0.19100227 0.17023090 0.15125134
[13] 0.17855019 0.06023773 0.52137996 0.85455350

But when I use the lm.influence() function
lm.influence(mt)$hat
I obtain:
 [1] 0.1735989 0.2999146 0.2334095 0.1455117 0.9216644 0.7553856
0.4486403
 [8] 0.2755802 0.4188349 0.1914242 0.1790093 0.1573939 0.1787553
0.1975511
[15] 0.5664988 0.8568274
mt is a model of the type y~x1+x2+x3+x4+x5, where y is:
y
[1]  17  17  35  69  69 173 173  17  17  73  17  35  69  35  35  52

As you see the differences are no too small.
Where is the problem? Is only a numerical stability problem?

Thank you very much for your help