dataframe - Error: Coefficients: (4 not defined because of singularities) in R -

i have error in code, couldn't figure out. have dataframe "a", with:

row.names      gm      variance     stddev      skewness   correltomarket  deratio 1   mmm     0.9785122   0.9998918   0.9999459   -1.049053   2.932738    0.07252799 

now, need find linear model above dataframe following code

riskmodel <- lm(formula=((a$gm)~(a$variance)+(a$skewness)+                          (a$correltomarket)+(a$deratio)),data=a) 

when run code, following summary "riskmodel"

call: lm(formula = ((a$gm) ~ (a$variance) + (a$skewness) + (a$correlationtomarket) +      (a$deratio)), data = a)  residuals: 1 residuals 0: no residual degrees of freedom!  coefficients: (4 not defined because of singularities)                       estimate std. error t value pr(>|t|) (intercept)             0.9785         na      na       na a$variance                  na         na      na       na a$skewness                  na         na      na       na a$correlationtomarket       na         na      na       na a$deratio                   na         na      na       na  residual standard error: nan on 0 degrees of freedom 

i don't understand why , grateful helps me this. have no idea whats going wrong.

you have single observation in data.frame. can't fit model 5 parameters single observation. need @ least 6 observations able fit parameters , have estimate of variance.