# Interpretation of ivreg() diagnostics in R

I'm trying to wrap my head around interpreting the diagnostics of the ivreg() command in R, from the {AER} package. Running the example code provided in the help page:

## data
data("CigarettesSW", package = "AER")
CigarettesSW$rprice <- with(CigarettesSW, price/cpi) CigarettesSW$rincome <- with(CigarettesSW, income/population/cpi)
CigarettesSW\$tdiff <- with(CigarettesSW, (taxs - tax)/cpi)

## model
fm <- ivreg(log(packs) ~ log(rprice) + log(rincome) | log(rincome) + tdiff + I(tax/cpi), data = CigarettesSW, subset = year == "1995")
summary(fm, vcov = sandwich, df = Inf, diagnostics = TRUE)


You get the following output:

Call:
ivreg(formula = log(packs) ~ log(rprice) + log(rincome) | log(rincome) +
tdiff + I(tax/cpi), data = CigarettesSW, subset = year ==
"1995")

Residuals:
Min         1Q     Median         3Q        Max
-0.6006931 -0.0862222 -0.0009999  0.1164699  0.3734227

Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept)    9.8950     0.9288  10.654  < 2e-16 ***
log(rprice)   -1.2774     0.2417  -5.286 1.25e-07 ***
log(rincome)   0.2804     0.2458   1.141    0.254

Diagnostic tests:
df1 df2 statistic p-value
Weak instruments   2  44   228.738  <2e-16 ***
Wu-Hausman         1  44     3.823  0.0569 .
Sargan             1  NA     0.333  0.5641


I'm interested in the interpretation of the diagnostic tests. Does this mean the instruments are weak or no? What does the Wu-Hausman mean, given that it is significant on 10% level? Sargan not being significant means what?